WorldWideScience

Sample records for feedback-based online network

  1. Stabilization of Networked Control Systems Under Feedback-based Communication

    National Research Council Canada - National Science Library

    Zhang, Lei; Hristu-Varsakelis, Dimitrios

    2004-01-01

    We study the stabilization of a networked control system (NSC) in which multiple sensors and actuators of a physical plant share a communication medium to exchange information with a remote controller...

  2. Multiple Description Coding with Feedback Based Network Compression

    DEFF Research Database (Denmark)

    Sørensen, Jesper Hemming; Østergaard, Jan; Popovski, Petar

    2010-01-01

    and an intermediate node, respectively. A trade-off exists between reducing the delay of the feedback by adapting in the vicinity of the receiver and increasing the gain from compression by adapting close to the source. The analysis shows that adaptation in the network provides a better trade-off than adaptation...

  3. Scheduling of network access for feedback-based embedded systems

    Science.gov (United States)

    Liberatore, Vincenzo

    2002-07-01

    nd communication capabilities. Examples range from smart dust embedded in building materials to networks of appliances in the home. Embedded devices will be deployed in unprecedented numbers, will enable pervasive distributed computing, and will radically change the way people interact with the surrounding environment [EGH00a]. The paper targets embedded systems and their real-time (RT) communication requirements. RT requirements arise from the

  4. An Enhanced Feedback-Base Downlink Packet Scheduling Algorithm for Mobile TV in WIMAX Networks

    Directory of Open Access Journals (Sweden)

    Joseph Oyewale

    2013-06-01

    Full Text Available With high speed access network technology like WIMAX, there is the need for efficient management of radio resources where the throughput and Qos requirements for Multicasting Broadcasting Services (MBS for example TV are to be met. An enhanced  feedback-base downlink Packet scheduling algorithm  that can be used in IEEE 802.16d/e networks for mobile TV “one way traffic”(MBS is needed to support many users utilizing multiuser diversity of the  broadband of WIMAX systems where a group of users(good/worst channels share allocated resources (bandwidth. This paper proposes a WIMAX framework feedback-base (like a channel-awareness downlink packet scheduling algorithm for Mobile TV traffics in IEEE806.16, in which network Physical Timing Slots (PSs resource blocks are allocated in a dynamic way to mobile TV subscribers based on the Channel State information (CSI feedback, and then considering users with worst channels with the aim of improving system throughput while system coverage is being guaranteed. The algorithm was examined by changing the PSs bandwidth allocation of the users and different number of users of a cell. Simulation results show our proposed algorithm performed better than other algorithms (blind algorithms in terms of improvement in system throughput performance. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso

  5. Online Advertising in Social Networks

    Science.gov (United States)

    Bagherjeiran, Abraham; Bhatt, Rushi P.; Parekh, Rajesh; Chaoji, Vineet

    Online social networks offer opportunities to analyze user behavior and social connectivity and leverage resulting insights for effective online advertising. This chapter focuses on the role of social network information in online display advertising.

  6. Online social support networks.

    Science.gov (United States)

    Mehta, Neil; Atreja, Ashish

    2015-04-01

    Peer support groups have a long history and have been shown to improve health outcomes. With the increasing familiarity with online social networks like Facebook and ubiquitous access to the Internet, online social support networks are becoming popular. While studies have shown the benefit of these networks in providing emotional support or meeting informational needs, robust data on improving outcomes such as a decrease in health services utilization or reduction in adverse outcomes is lacking. These networks also pose unique challenges in the areas of patient privacy, funding models, quality of content, and research agendas. Addressing these concerns while creating patient-centred, patient-powered online support networks will help leverage these platforms to complement traditional healthcare delivery models in the current environment of value-based care.

  7. A Feedback-Based Secure Path Approach for Wireless Sensor Network Data Collection

    Science.gov (United States)

    Mao, Yuxin; Wei, Guiyi

    2010-01-01

    The unattended nature of wireless sensor networks makes them very vulnerable to malicious attacks. Therefore, how to preserve secure data collection is an important issue to wireless sensor networks. In this paper, we propose a novel approach of secure data collection for wireless sensor networks. We explore secret sharing and multipath routing to achieve secure data collection in wireless sensor network with compromised nodes. We present a novel tracing-feedback mechanism, which makes full use of the routing functionality of wireless sensor networks, to improve the quality of data collection. The major advantage of the approach is that the secure paths are constructed as a by-product of data collection. The process of secure routing causes little overhead to the sensor nodes in the network. Compared with existing works, the algorithms of the proposed approach are easy to implement and execute in resource-constrained wireless sensor networks. According to the result of a simulation experiment, the performance of the approach is better than the recent approaches with a similar purpose. PMID:22163424

  8. A Feedback-Based Secure Path Approach for Wireless Sensor Network Data Collection

    Directory of Open Access Journals (Sweden)

    Guiyi Wei

    2010-10-01

    Full Text Available The unattended nature of wireless sensor networks makes them very vulnerable to malicious attacks. Therefore, how to preserve secure data collection is an important issue to wireless sensor networks. In this paper, we propose a novel approach of secure data collection for wireless sensor networks. We explore secret sharing and multipath routing to achieve secure data collection in wireless sensor network with compromised nodes. We present a novel tracing-feedback mechanism, which makes full use of the routing functionality of wireless sensor networks, to improve the quality of data collection. The major advantage of the approach is that the secure paths are constructed as a by-product of data collection. The process of secure routing causes little overhead to the sensor nodes in the network. Compared with existing works, the algorithms of the proposed approach are easy to implement and execute in resource-constrained wireless sensor networks. According to the result of a simulation experiment, the performance of the approach is better than the recent approaches with a similar purpose.

  9. A feedback-based secure path approach for wireless sensor network data collection.

    Science.gov (United States)

    Mao, Yuxin; Wei, Guiyi

    2010-01-01

    The unattended nature of wireless sensor networks makes them very vulnerable to malicious attacks. Therefore, how to preserve secure data collection is an important issue to wireless sensor networks. In this paper, we propose a novel approach of secure data collection for wireless sensor networks. We explore secret sharing and multipath routing to achieve secure data collection in wireless sensor network with compromised nodes. We present a novel tracing-feedback mechanism, which makes full use of the routing functionality of wireless sensor networks, to improve the quality of data collection. The major advantage of the approach is that the secure paths are constructed as a by-product of data collection. The process of secure routing causes little overhead to the sensor nodes in the network. Compared with existing works, the algorithms of the proposed approach are easy to implement and execute in resource-constrained wireless sensor networks. According to the result of a simulation experiment, the performance of the approach is better than the recent approaches with a similar purpose.

  10. Foraging Online Social Networks

    NARCIS (Netherlands)

    Koot, G.; Huis in ’t Veld, M.A.A.; Hendricksen, J.; Vries, A. de; Broek, E.L. van den

    2014-01-01

    A concise and practical introduction is given on Online Social Networks (OSN) and their application in law enforcement, including a brief survey of related work. Subsequently, a tool is introduced that can be used to search OSN in order to generate user profiles. Both its architecture and processing

  11. LHCb Online Networking Requirements

    CERN Document Server

    Jost, B

    2003-01-01

    This document describes the networking requirements of the LHCb online installation. It lists both quantitative aspects such as the number of required switch ports, as well as some qualitative features of the equipment, such as minimum buffer sizes in switches. The document comprises both the data acquisition network and the controls/general-purpose network. While the numbers represent our best current knowledge and are intended to give (in particular) network equipment manufacturers an overview of our needs, this document should not be confused with a market survey questionnaire or a formal tendering document. However the information contained in this document will be the input of any such document. A preliminary schedule for procurement and installation is also given.

  12. Online social networking for radiology.

    Science.gov (United States)

    Auffermann, William F; Chetlen, Alison L; Colucci, Andrew T; DeQuesada, Ivan M; Grajo, Joseph R; Heller, Matthew T; Nowitzki, Kristina M; Sherry, Steven J; Tillack, Allison A

    2015-01-01

    Online social networking services have changed the way we interact as a society and offer many opportunities to improve the way we practice radiology and medicine in general. This article begins with an introduction to social networking. Next, the latest advances in online social networking are reviewed, and areas where radiologists and clinicians may benefit from these new tools are discussed. This article concludes with several steps that the interested reader can take to become more involved in online social networking. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

  13. Online Identities and Social Networking

    Science.gov (United States)

    Maheswaran, Muthucumaru; Ali, Bader; Ozguven, Hatice; Lord, Julien

    Online identities play a critical role in the social web that is taking shape on the Internet. Despite many technical proposals for creating and managing online identities, none has received widespread acceptance. Design and implementation of online identities that are socially acceptable on the Internet remains an open problem. This chapter discusses the interplay between online identities and social networking. Online social networks (OSNs) are growing at a rapid pace and has millions of members in them. While the recent trend is to create explicit OSNs such as Facebook and MySpace, we also have implicit OSNs such as interaction graphs created by email and instant messaging services. Explicit OSNs allow users to create profiles and use them to project their identities on the web. There are many interesting identity related issues in the context of social networking including how OSNs help and hinder the definition of online identities.

  14. Online networks destroy social trust

    OpenAIRE

    Sabatini, Fabio; Sarracino, Francesco

    2014-01-01

    Studies in the social capital literature have documented two stylised facts: first, a decline in measures of social participation has occurred in many OECD countries. Second, and more recently, the success of social networking sites (SNSs) has resulted in a steep rise in online social participation. Our study adds to this body of research by conducting the first empirical assessment of how online networking affects two economically relevant aspects of social capital, i.e. trust and sociabilit...

  15. Measurement of Online Social Networks

    Science.gov (United States)

    Gjoka, Mina

    2010-01-01

    In recent years, the popularity of online social networks (OSN) has risen to unprecedented levels, with the most popular ones having hundreds of millions of users. This success has generated interest within the networking community and has given rise to a number of measurement and characterization studies, which provide a first step towards their…

  16. Privacy in Online Social Networks

    NARCIS (Netherlands)

    Beye, Michael; Jeckmans, Arjan; Erkin, Zekeriya; Erkin, Zekeriya; Hartel, Pieter H.; Lagendijk, Reginald; Tang, Qiang; Abraham, A.

    Online Social Networks (OSNs) have become part of daily life for millions of users. Users building explicit networks that represent their social relationships and often share a wealth of personal information to their own benefit. The potential privacy risks of such behavior are often underestimated

  17. Modeling online social signed networks

    Science.gov (United States)

    Li, Le; Gu, Ke; Zeng, An; Fan, Ying; Di, Zengru

    2018-04-01

    People's online rating behavior can be modeled by user-object bipartite networks directly. However, few works have been devoted to reveal the hidden relations between users, especially from the perspective of signed networks. We analyze the signed monopartite networks projected by the signed user-object bipartite networks, finding that the networks are highly clustered with obvious community structure. Interestingly, the positive clustering coefficient is remarkably higher than the negative clustering coefficient. Then, a Signed Growing Network model (SGN) based on local preferential attachment is proposed to generate a user's signed network that has community structure and high positive clustering coefficient. Other structural properties of the modeled networks are also found to be similar to the empirical networks.

  18. Online Social Network Interactions:

    Directory of Open Access Journals (Sweden)

    Hui-Jung Chang

    2018-01-01

    Full Text Available A cross-cultural comparison of social networking structure on McDonald’s Facebook fan sites between Taiwan and the USA was conducted utilizing the individualism/collectivism dimension proposed by Hofstede. Four network indicators are used to describe the network structure of McDonald’s Facebook fan sites: size, density, clique and centralization. Individuals who post on both Facebook sites for the year of 2012 were considered as network participants for the purpose of the study. Due to the huge amount of data, only one thread of postings was sampled from each month of the year of 2012. The final data consists of 1002 postings written by 896 individuals and 5962 postings written by 5532 individuals from Taiwan and the USA respectively. The results indicated that the USA McDonald’s Facebook fan network has more fans, while Taiwan’s McDonald’s Facebook fan network is more densely connected. Cliques did form among the overall multiplex and within the individual uniplex networks in two countries, yet no significant differences were found between them. All the fan networks in both countries are relatively centralized, mostly on the site operators.

  19. Barter Online Network

    Directory of Open Access Journals (Sweden)

    Van Ngoc Tran

    2015-12-01

    Full Text Available Barter is the direct exchange of goods or services without using a medium of exchange, such as money. Barter faced a number of limitations, and according to Smith (1776, these limitations led to the emergence of money. However, trading with money also exposes traders to the problems of monetary economy such as inflation, deflation, currency de-valuation, and currency exchange fluctuation. According to Statista.com (2015, in 2016, global Business to Customer (B2C e-commerce sales will reach 1.92 trillion US dollars. On the other hand, online barter solutions are rare on the market. The only attempts to tackle online barter are mobile applications, carried out by small businesses. The market gap is caused by the unsolved inefficiencies of barter. The aim of this thesis is to identify the problems of barter, propose an IT solution for the problems of barter, and finally, produce an artefact, which is the realisation of the proposed IT solution by utilising computer systems and computer algorithms.

  20. The ESID Online Database network.

    Science.gov (United States)

    Guzman, D; Veit, D; Knerr, V; Kindle, G; Gathmann, B; Eades-Perner, A M; Grimbacher, B

    2007-03-01

    Primary immunodeficiencies (PIDs) belong to the group of rare diseases. The European Society for Immunodeficiencies (ESID), is establishing an innovative European patient and research database network for continuous long-term documentation of patients, in order to improve the diagnosis, classification, prognosis and therapy of PIDs. The ESID Online Database is a web-based system aimed at data storage, data entry, reporting and the import of pre-existing data sources in an enterprise business-to-business integration (B2B). The online database is based on Java 2 Enterprise System (J2EE) with high-standard security features, which comply with data protection laws and the demands of a modern research platform. The ESID Online Database is accessible via the official website (http://www.esid.org/). Supplementary data are available at Bioinformatics online.

  1. What Online Networks Offer: "Online Network Compositions and Online Learning Experiences of Three Ethnic Groups"

    Science.gov (United States)

    Lecluijze, Suzanne Elisabeth; de Haan, Mariëtte; Ünlüsoy, Asli

    2015-01-01

    This exploratory study examines ethno-cultural diversity in youth's narratives regarding their "online" learning experiences while also investigating how these narratives can be understood from the analysis of their online network structure and composition. Based on ego-network data of 79 respondents this study compared the…

  2. Recommendation in evolving online networks

    Science.gov (United States)

    Hu, Xiao; Zeng, An; Shang, Ming-Sheng

    2016-02-01

    Recommender system is an effective tool to find the most relevant information for online users. By analyzing the historical selection records of users, recommender system predicts the most likely future links in the user-item network and accordingly constructs a personalized recommendation list for each user. So far, the recommendation process is mostly investigated in static user-item networks. In this paper, we propose a model which allows us to examine the performance of the state-of-the-art recommendation algorithms in evolving networks. We find that the recommendation accuracy in general decreases with time if the evolution of the online network fully depends on the recommendation. Interestingly, some randomness in users' choice can significantly improve the long-term accuracy of the recommendation algorithm. When a hybrid recommendation algorithm is applied, we find that the optimal parameter gradually shifts towards the diversity-favoring recommendation algorithm, indicating that recommendation diversity is essential to keep a high long-term recommendation accuracy. Finally, we confirm our conclusions by studying the recommendation on networks with the real evolution data.

  3. Identifying Gatekeepers in Online Learning Networks

    Science.gov (United States)

    Gursakal, Necmi; Bozkurt, Aras

    2017-01-01

    The rise of the networked society has not only changed our perceptions but also the definitions, roles, processes and dynamics of online learning networks. From offline to online worlds, networks are everywhere and gatekeepers are an important entity in these networks. In this context, the purpose of this paper is to explore gatekeeping and…

  4. The Structure of Online Consumer Communication Networks

    NARCIS (Netherlands)

    B.G.C. Dellaert (Benedict); M.J.W. Harmsen-van Hout (Marjolein); P.J.J. Herings (Jean-Jacques)

    2006-01-01

    textabstractIn this paper we study the structure of the bilateral communication links within Online Consumer Communication Networks (OCCNs), such as virtual communities. Compared to the offline world, consumers in online networks are highly flexible to choose their communication partners and little

  5. The Deep Structure of Organizational Online Networking

    DEFF Research Database (Denmark)

    Trier, Matthias; Richter, Alexander

    2015-01-01

    While research on organizational online networking recently increased significantly, most studies adopt quantitative research designs with a focus on the consequences of social network configurations. Very limited attention is paid to comprehensive theoretical conceptions of the complex phenomenon...... of organizational online networking. We address this gap by adopting a theoretical framework of the deep structure of organizational online networking with a focus on their emerging meaning for the employees. We apply and assess the framework in a qualitative case study of a large-scale implementation...... of a corporate social network site (SNS) in a global organization. We reveal organizational online networking as a multi-dimensional phenomenon with multiplex relationships that are unbalanced, primarily consist of weak ties and are subject to temporal change. Further, we identify discourse drivers...

  6. Modelling Users` Trust in Online Social Networks

    Directory of Open Access Journals (Sweden)

    Iacob Cătoiu

    2014-02-01

    Full Text Available Previous studies (McKnight, Lankton and Tripp, 2011; Liao, Lui and Chen, 2011 have shown the crucial role of trust when choosing to disclose sensitive information online. This is the case of online social networks users, who must disclose a certain amount of personal data in order to gain access to these online services. Taking into account privacy calculus model and the risk/benefit ratio, we propose a model of users’ trust in online social networks with four variables. We have adapted metrics for the purpose of our study and we have assessed their reliability and validity. We use a Partial Least Squares (PLS based structural equation modelling analysis, which validated all our initial assumptions, indicating that our three predictors (privacy concerns, perceived benefits and perceived risks explain 48% of the variation of users’ trust in online social networks, the resulting variable of our study. We also discuss the implications and further research opportunities of our study.

  7. Online Social Networking: Usage in Adolescents

    Science.gov (United States)

    Raju, Nevil Johnson; Valsaraj, Blessy Prabha; Noronha, Judith

    2015-01-01

    Online social networking (OSN) has played a significant role on the relationship among college students. It is becoming a popular medium for socializing online and tools to facilitate friendship. Young adults and adolescents are the most prolific users of OSN sites. The frequent use of OSN sites results in addiction toward these sites and…

  8. Online Social Networking: A Primer for Radiology

    OpenAIRE

    Prasanna, Prasanth M.; Seagull, F. Jacob; Nagy, Paul

    2011-01-01

    Online social networking is an immature, but rapidly evolving industry of web-based technologies that allow individuals to develop online relationships. News stories populate the headlines about various websites which can facilitate patient and doctor interaction. There remain questions about protecting patient confidentiality and defining etiquette in order to preserve the doctor/patient relationship and protect physicians. How much social networking-based communication or other forms of E-c...

  9. Evolution of a large online social network

    International Nuclear Information System (INIS)

    Hu Haibo; Wang Xiaofan

    2009-01-01

    Although recently there are extensive research on the collaborative networks and online communities, there is very limited knowledge about the actual evolution of the online social networks (OSN). In the Letter, we study the structural evolution of a large online virtual community. We find that the scale growth of the OSN shows non-trivial S shape which may provide a proper exemplification for Bass diffusion model. We reveal that the evolutions of many network properties, such as density, clustering, heterogeneity and modularity, show non-monotone feature, and shrink phenomenon occurs for the path length and diameter of the network. Furthermore, the OSN underwent a transition from degree assortativity characteristic of collaborative networks to degree disassortativity characteristic of many OSNs. Our study has revealed the evolutionary pattern of interpersonal interactions in a specific population and provided a valuable platform for theoretical modeling and further analysis

  10. Online professional networks for physicians: risk management.

    Science.gov (United States)

    Hyman, Jon L; Luks, Howard J; Sechrest, Randale

    2012-05-01

    The rapidly developing array of online physician-only communities represents a potential extraordinary advance in the availability of educational and informational resources to physicians. These online communities provide physicians with a new range of controls over the information they process, but use of this social media technology carries some risk. The purpose of this review was to help physicians manage the risks of online professional networking and discuss the potential benefits that may come with such networks. This article explores the risks and benefits of physicians engaging in online professional networking with peers and provides suggestions on risk management. Through an Internet search and literature review, we scrutinized available case law, federal regulatory code, and guidelines of conduct from professional organizations and consultants. We reviewed the OrthoMind.com site as a case example because it is currently the only online social network exclusively for orthopaedic surgeons. Existing case law suggests potential liability for orthopaedic surgeons who engage with patients on openly accessible social network platforms. Current society guidelines in both the United States and Britain provide sensible rules that may mitigate such risks. However, the overall lack of a strong body of legal opinions, government regulations as well as practical experience for most surgeons limit the suitability of such platforms. Closed platforms that are restricted to validated orthopaedic surgeons may limit these downside risks and hence allow surgeons to collaborate with one another both as clinicians and practice owners. Educating surgeons about the pros and cons of participating in these networking platforms is helping them more astutely manage risks and optimize benefits. This evolving online environment of professional interaction is one of few precedents, but the application of risk management strategies that physicians use in daily practice carries over

  11. Content Propagation in Online Social Networks

    NARCIS (Netherlands)

    Blenn, N.

    2014-01-01

    This thesis presents methods and techniques to analyze content propagation within online social networks (OSNs) using a graph theoretical approach. Important factors and different techniques to analyze and describe content propagation, starting from the smallest entity in a network, representing a

  12. Information diffusion in structured online social networks

    Science.gov (United States)

    Li, Pei; Zhang, Yini; Qiao, Fengcai; Wang, Hui

    2015-05-01

    Nowadays, due to the word-of-mouth effect, online social networks have been considered to be efficient approaches to conduct viral marketing, which makes it of great importance to understand the diffusion dynamics in online social networks. However, most research on diffusion dynamics in epidemiology and existing social networks cannot be applied directly to characterize online social networks. In this paper, we propose models to characterize the information diffusion in structured online social networks with push-based forwarding mechanism. We introduce the term user influence to characterize the average number of times that messages are browsed which is incurred by a given type user generating a message, and study the diffusion threshold, above which the user influence of generating a message will approach infinity. We conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of use in understanding the diffusion dynamics in online social networks and also critical for advertisers in viral marketing who want to estimate the user influence before posting an advertisement.

  13. Online social network data as sociometric markers.

    Science.gov (United States)

    Binder, Jens F; Buglass, Sarah L; Betts, Lucy R; Underwood, Jean D M

    2017-10-01

    Data from online social networks carry enormous potential for psychological research, yet their use and the ethical implications thereof are currently hotly debated. The present work aims to outline in detail the unique information richness of this data type and, in doing so, to support researchers when deciding on ethically appropriate ways of collecting, storing, publishing, and sharing data from online sources. Focusing on the very nature of social networks, their structural characteristics, and depth of information, we provide a detailed and accessible account of the challenges associated with data management and data storage. In particular, the general nonanonymity of network data sets is discussed, and an approach is developed to quantify the level of uniqueness that a particular online network bestows upon the individual maintaining it. Using graph enumeration techniques, we show that comparatively sparse information on a network is suitable as a sociometric marker that allows for the identification of an individual from the global population of online users. The impossibility of anonymizing specific types of network data carries implications for ethical guidelines and research practice. At the same time, network uniqueness opens up opportunities for novel research in psychology. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  14. Benford's Law Applies to Online Social Networks.

    Science.gov (United States)

    Golbeck, Jennifer

    2015-01-01

    Benford's Law states that, in naturally occurring systems, the frequency of numbers' first digits is not evenly distributed. Numbers beginning with a 1 occur roughly 30% of the time, and are six times more common than numbers beginning with a 9. We show that Benford's Law applies to social and behavioral features of users in online social networks. Using social data from five major social networks (Facebook, Twitter, Google Plus, Pinterest, and LiveJournal), we show that the distribution of first significant digits of friend and follower counts for users in these systems follow Benford's Law. The same is true for the number of posts users make. We extend this to egocentric networks, showing that friend counts among the people in an individual's social network also follows the expected distribution. We discuss how this can be used to detect suspicious or fraudulent activity online and to validate datasets.

  15. Benford's Law Applies to Online Social Networks.

    Directory of Open Access Journals (Sweden)

    Jennifer Golbeck

    Full Text Available Benford's Law states that, in naturally occurring systems, the frequency of numbers' first digits is not evenly distributed. Numbers beginning with a 1 occur roughly 30% of the time, and are six times more common than numbers beginning with a 9. We show that Benford's Law applies to social and behavioral features of users in online social networks. Using social data from five major social networks (Facebook, Twitter, Google Plus, Pinterest, and LiveJournal, we show that the distribution of first significant digits of friend and follower counts for users in these systems follow Benford's Law. The same is true for the number of posts users make. We extend this to egocentric networks, showing that friend counts among the people in an individual's social network also follows the expected distribution. We discuss how this can be used to detect suspicious or fraudulent activity online and to validate datasets.

  16. Managing Trust in Online Social Networks

    Science.gov (United States)

    Bhuiyan, Touhid; Josang, Audun; Xu, Yue

    In recent years, there is a dramatic growth in number and popularity of online social networks. There are many networks available with more than 100 million registered users such as Facebook, MySpace, QZone, Windows Live Spaces etc. People may connect, discover and share by using these online social networks. The exponential growth of online communities in the area of social networks attracts the attention of the researchers about the importance of managing trust in online environment. Users of the online social networks may share their experiences and opinions within the networks about an item which may be a product or service. The user faces the problem of evaluating trust in a service or service provider before making a choice. Recommendations may be received through a chain of friends network, so the problem for the user is to be able to evaluate various types of trust opinions and recommendations. This opinion or recommendation has a great influence to choose to use or enjoy the item by the other user of the community. Collaborative filtering system is the most popular method in recommender system. The task in collaborative filtering is to predict the utility of items to a particular user based on a database of user rates from a sample or population of other users. Because of the different taste of different people, they rate differently according to their subjective taste. If two people rate a set of items similarly, they share similar tastes. In the recommender system, this information is used to recommend items that one participant likes, to other persons in the same cluster. But the collaborative filtering system performs poor when there is insufficient previous common rating available between users; commonly known as cost start problem. To overcome the cold start problem and with the dramatic growth of online social networks, trust based approach to recommendation has emerged. This approach assumes a trust network among users and makes recommendations

  17. Structural Changes in Online Discussion Networks

    DEFF Research Database (Denmark)

    Yang, Yang; Medaglia, Rony

    2014-01-01

    Social networking platforms in China provide a hugely interesting and relevant source for understanding dynamics of online discussions in a unique socio-cultural and institutional environment. This paper investigates the evolution of patterns of similar-minded and different-minded interactions ov...

  18. Community Structure in Online Collegiate Social Networks

    Science.gov (United States)

    Traud, Amanda; Kelsic, Eric; Mucha, Peter; Porter, Mason

    2009-03-01

    Online social networking sites have become increasingly popular with college students. The networks we studied are defined through ``friendships'' indicated by Facebook users from UNC, Oklahoma, Caltech, Georgetown, and Princeton. We apply the tools of network science to study the Facebook networks from these five different universities at a single point in time. We investigate each single-institution network's community structure, which we obtain through partitioning the graph using an eigenvector method. We use both graphical and quantitative tools, including pair-counting methods, which we interpret through statistical analysis and permutation tests to measure the correlations between the network communities and a set of characteristics given by each user (residence, class year, major, and high school). We also analyze the single gender subsets of these networks, and the impact of missing demographical data. Our study allows us to compare the online social networks for the five schools as well as infer differences in offline social interactions. At the schools studied, we were able to define which characteristics of the Facebook users correlate best with friendships.

  19. A framework for online social networking features

    Directory of Open Access Journals (Sweden)

    Mohsen Shafiei Nikabadi

    2014-06-01

    Full Text Available Social networks form a basis for maintaining social contacts, finding users with common interests, creating local content and sharing information. Recently networks have created a fundamental framework for analyzing and modeling the complex systems. Users' behavior studies and evaluates the system performance and leads to better planning and implementation of advertising policies on the web sites. Therefore, this study offers a framework for online social networks' characteristics. In terms of objective, this survey is practical descriptive. Sampling has been done among 384 of graduate students who have good experiences of membership in online social network. Confirmatory factor analysis is used to evaluate the validity of variables in research model. Characteristics of online social networks are defined based on six components and framework's indexes are analyzed through factor analysis. The reliability is calculated separately for each dimension and since they are all above 0.7, the reliability of the study can be confirmed. According to our research results, in terms of size, the number of people who apply for membership in various online social networking is an important index. In terms of individual preference to connect with, people who are relative play essential role in social network development. In terms of homogeneity variable, the number of people who visit their friends’ pages is important for measuring frequency variable. In terms of frequency, the use of entertainment and recreation services is more important index. In terms of proximity, being in the same city is a more important index and index of creating a sense of belonging and confidence is more important for measuring reciprocity variable.

  20. Link prediction in multiplex online social networks

    Science.gov (United States)

    Jalili, Mahdi; Orouskhani, Yasin; Asgari, Milad; Alipourfard, Nazanin; Perc, Matjaž

    2017-02-01

    Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%.

  1. Mining Trust Relationships from Online Social Networks

    Institute of Scientific and Technical Information of China (English)

    Yu Zhang; Tong Yu

    2012-01-01

    With the growing popularity of online social network,trust plays a more and more important role in connecting people to each other.We rely on our personal trust to accept recommendations,to make purchase decisions and to select transaction partners in the online community.Therefore,how to obtain trust relationships through mining online social networks becomes an important research topic.There are several shortcomings of existing trust mining methods.First,trust is category-dependent.However,most of the methods overlook the category attribute of trust relationships,which leads to low accuracy in trust calculation.Second,since the data in online social networks cannot be understood and processed by machines directly,traditional mining methods require much human effort and are not easily applied to other applications.To solve the above problems,we propose a semantic-based trust reasoning mechanism to mine trust relationships from online social networks automatically.We emphasize the category attribute of pairwise relationships and utilize Semantic Web technologies to build a domain ontology for data communication and knowledge sharing.We exploit role-based and behavior-based reasoning functions to infer implicit trust relationships and category-specific trust relationships.We make use of path expressions to extend reasoning rules so that the mining process can be done directly without much human effort.We perform experiments on real-life data extracted from Epinions.The experimental results verify the effectiveness and wide application use of our proposed method.

  2. Security and trust in online social networks

    CERN Document Server

    Carminati, Barbara; Viviani, Marco; Viviani, Marco; Carminati, Barbara

    2013-01-01

    The enormous success and diffusion that online social networks (OSNs) are encountering nowadays is vastly apparent. Users' social interactions now occur using online social media as communication channels; personal information and activities are easily exchanged both for recreational and business purposes in order to obtain social or economic advantages. In this scenario, OSNs are considered critical applications with respect to the security of users and their resources, for their characteristics alone: the large amount of personal information they manage, big economic upturn connected to thei

  3. Online social networking: a primer for radiology.

    Science.gov (United States)

    Prasanna, Prasanth M; Seagull, F Jacob; Nagy, Paul

    2011-10-01

    Online social networking is an immature, but rapidly evolving industry of web-based technologies that allow individuals to develop online relationships. News stories populate the headlines about various websites which can facilitate patient and doctor interaction. There remain questions about protecting patient confidentiality and defining etiquette in order to preserve the doctor/patient relationship and protect physicians. How much social networking-based communication or other forms of E-communication is effective? What are the potential benefits and pitfalls of this form of communication? Physicians are exploring how social networking might provide a forum for interacting with their patients, and advance collaborative patient care. Several organizations and institutions have set forth policies to address these questions and more. Though still in its infancy, this form of media has the power to revolutionize the way physicians interact with their patients and fellow health care workers. In the end, physicians must ask what value is added by engaging patients or other health care providers in a social networking format. Social networks may flourish in health care as a means of distributing information to patients or serve mainly as support groups among patients. Physicians must tread a narrow path to bring value to interactions in these networks while limiting their exposure to unwanted liability.

  4. From Offline Social Networks to Online Social Networks: Changes in Entrepreneurship

    Directory of Open Access Journals (Sweden)

    Yang SONG

    2015-01-01

    Full Text Available The paper reviewed studies of entrepreneurship based on the emergency of online social networks. Similar to offline social networks, entrepreneurs’ online social networks have their own unique characteristics. We first reviewed the offline network based research on entrepreneurship. Then we reviewed the studies of entrepreneurship in the context of online social networks including those focusing on topics of network structures and network ties. We highlighted online network communities based on the data collected from LinkedIn, Facebook and Twitter. Our research implies that both researcher and entrepreneurs are facing new opportunities due to the emergence of online social networks.

  5. Measurements and analysis of online social networks

    OpenAIRE

    González Sánchez, Roberto

    2014-01-01

    Mención Internacional Online Social Networks (OSNs) have become the most used Internet applications attracting hundreds of millions active users every day. The large amount of valuable information in OSNs (not even before available) has attracted the research community to design sophisticated techniques to collect, process, interpret and apply these data into a large range of disciplines including Sociology, Marketing, Computer Science, etc. This thesis presents a series of ...

  6. Online Customization and Enrollment Application Network (OCEAN

    Directory of Open Access Journals (Sweden)

    E. Kongar

    2007-09-01

    Full Text Available This paper introduces the Online Customization and Enrollment Application Network (OCEAN, developed in the School of Engineering at the University of Bridgeport. OCEAN is an interactive web-based application for graduate programs, concentrations, certificates and courses across the Schools of Engineering, Business and Education that allows prospective and current students to customize their preferences in the course selection process depending on the targeted graduate concentrations, degrees, and/or dual degree programs.

  7. Discrete Opinion Dynamics on Online Social Networks

    Science.gov (United States)

    Hu, Yan-Li; Bai, Liang; Zhang, Wei-Ming

    2013-01-01

    This paper focuses on the dynamics of binary opinions {+1, -1} on online social networks consisting of heterogeneous actors. In our model, actors update their opinions under the interplay of social influence and self- affirmation, which leads to rich dynamical behaviors on online social networks. We find that the opinion leading to the consensus features an advantage of the initially weighted fraction based on actors' strength over the other, instead of the population. For the role of specific actors, the consensus converges towards the opinion that a small fraction of high-strength actors hold, and individual diversity of self-affirmation slows down the ordering process of consensus. These indicate that high-strength actors play an essential role in opinion formation with strong social influence as well as high persistence. Further investigations show that the initial fraction of high-strength actors to dominate the evolution depends on the heterogeneity of the strength distribution, and less high-strength actors are needed in the case of a smaller exponent of power-law distribution of actors' strength. Our study provides deep insights into the role of social influence and self-affirmation on opinion formation on online social networks.

  8. Discrete Opinion Dynamics on Online Social Networks

    International Nuclear Information System (INIS)

    Hu Yan-Li; Bai Liang; Zhang Wei-Ming

    2013-01-01

    This paper focuses on the dynamics of binary opinions {+1, −1} on online social networks consisting of heterogeneous actors. In our model, actors update their opinions under the interplay of social influence and self- affirmation, which leads to rich dynamical behaviors on online social networks. We find that the opinion leading to the consensus features an advantage of the initially weighted fraction based on actors' strength over the other, instead of the population. For the role of specific actors, the consensus converges towards the opinion that a small fraction of high-strength actors hold, and individual diversity of self-affirmation slows down the ordering process of consensus. These indicate that high-strength actors play an essential role in opinion formation with strong social influence as well as high persistence. Further investigations show that the initial fraction of high-strength actors to dominate the evolution depends on the heterogeneity of the strength distribution, and less high-strength actors are needed in the case of a smaller exponent of power-law distribution of actors' strength. Our study provides deep insights into the role of social influence and self-affirmation on opinion formation on online social networks. (general)

  9. An evolving model of online bipartite networks

    Science.gov (United States)

    Zhang, Chu-Xu; Zhang, Zi-Ke; Liu, Chuang

    2013-12-01

    Understanding the structure and evolution of online bipartite networks is a significant task since they play a crucial role in various e-commerce services nowadays. Recently, various attempts have been tried to propose different models, resulting in either power-law or exponential degree distributions. However, many empirical results show that the user degree distribution actually follows a shifted power-law distribution, the so-called Mandelbrot’s law, which cannot be fully described by previous models. In this paper, we propose an evolving model, considering two different user behaviors: random and preferential attachment. Extensive empirical results on two real bipartite networks, Delicious and CiteULike, show that the theoretical model can well characterize the structure of real networks for both user and object degree distributions. In addition, we introduce a structural parameter p, to demonstrate that the hybrid user behavior leads to the shifted power-law degree distribution, and the region of power-law tail will increase with the increment of p. The proposed model might shed some lights in understanding the underlying laws governing the structure of real online bipartite networks.

  10. Online Social Networking and Mental Health

    Science.gov (United States)

    2014-01-01

    Abstract During the past decade, online social networking has caused profound changes in the way people communicate and interact. It is unclear, however, whether some of these changes may affect certain normal aspects of human behavior and cause psychiatric disorders. Several studies have indicated that the prolonged use of social networking sites (SNS), such as Facebook, may be related to signs and symptoms of depression. In addition, some authors have indicated that certain SNS activities might be associated with low self-esteem, especially in children and adolescents. Other studies have presented opposite results in terms of positive impact of social networking on self-esteem. The relationship between SNS use and mental problems to this day remains controversial, and research on this issue is faced with numerous challenges. This concise review focuses on the recent findings regarding the suggested connection between SNS and mental health issues such as depressive symptoms, changes in self-esteem, and Internet addiction. PMID:25192305

  11. Online social networking and mental health.

    Science.gov (United States)

    Pantic, Igor

    2014-10-01

    During the past decade, online social networking has caused profound changes in the way people communicate and interact. It is unclear, however, whether some of these changes may affect certain normal aspects of human behavior and cause psychiatric disorders. Several studies have indicated that the prolonged use of social networking sites (SNS), such as Facebook, may be related to signs and symptoms of depression. In addition, some authors have indicated that certain SNS activities might be associated with low self-esteem, especially in children and adolescents. Other studies have presented opposite results in terms of positive impact of social networking on self-esteem. The relationship between SNS use and mental problems to this day remains controversial, and research on this issue is faced with numerous challenges. This concise review focuses on the recent findings regarding the suggested connection between SNS and mental health issues such as depressive symptoms, changes in self-esteem, and Internet addiction.

  12. Collective iteration behavior for online social networks

    Science.gov (United States)

    Liu, Jian-Guo; Li, Ren-De; Guo, Qiang; Zhang, Yi-Cheng

    2018-06-01

    Understanding the patterns of collective behavior in online social network (OSNs) is critical to expanding the knowledge of human behavior and tie relationship. In this paper, we investigate a specific pattern called social signature in Facebook and Wiki users' online communication behaviors, capturing the distribution of frequency of interactions between different alters over time in the ego network. The empirical results show that there are robust social signatures of interactions no matter how friends change over time, which indicates that a stable commutation pattern exists in online communication. By comparing a random null model, we find the that commutation pattern is heterogeneous between ego and alters. Furthermore, in order to regenerate the pattern of the social signature, we present a preferential interaction model, which assumes that new users intend to look for the old users with strong ties while old users have tendency to interact with new friends. The experimental results show that the presented model can reproduce the heterogeneity of social signature by adjusting 2 parameters, the number of communicating targets m and the max number of interactions n, for Facebook users, m = n = 5, for Wiki users, m = 2 and n = 8. This work helps in deeply understanding the regularity of social signature.

  13. Data Quality in Online Health Social Networks for Chronic Diseases

    Science.gov (United States)

    Venkatesan, Srikanth

    2017-01-01

    Can medical advice from other participants in online health social networks impact patient safety? What can we do alleviate this problem? How does the accuracy of information on such networks affect the patients?. There has been a significant increase , in recent years, in the use of online health social network sites as more patients seek to…

  14. Anatomy of an online misinformation network.

    Directory of Open Access Journals (Sweden)

    Chengcheng Shao

    Full Text Available Massive amounts of fake news and conspiratorial content have spread over social media before and after the 2016 US Presidential Elections despite intense fact-checking efforts. How do the spread of misinformation and fact-checking compete? What are the structural and dynamic characteristics of the core of the misinformation diffusion network, and who are its main purveyors? How to reduce the overall amount of misinformation? To explore these questions we built Hoaxy, an open platform that enables large-scale, systematic studies of how misinformation and fact-checking spread and compete on Twitter. Hoaxy captures public tweets that include links to articles from low-credibility and fact-checking sources. We perform k-core decomposition on a diffusion network obtained from two million retweets produced by several hundred thousand accounts over the six months before the election. As we move from the periphery to the core of the network, fact-checking nearly disappears, while social bots proliferate. The number of users in the main core reaches equilibrium around the time of the election, with limited churn and increasingly dense connections. We conclude by quantifying how effectively the network can be disrupted by penalizing the most central nodes. These findings provide a first look at the anatomy of a massive online misinformation diffusion network.

  15. Anatomy of an online misinformation network

    Science.gov (United States)

    Wang, Lei; Jiang, Xinwen; Flammini, Alessandro; Ciampaglia, Giovanni Luca

    2018-01-01

    Massive amounts of fake news and conspiratorial content have spread over social media before and after the 2016 US Presidential Elections despite intense fact-checking efforts. How do the spread of misinformation and fact-checking compete? What are the structural and dynamic characteristics of the core of the misinformation diffusion network, and who are its main purveyors? How to reduce the overall amount of misinformation? To explore these questions we built Hoaxy, an open platform that enables large-scale, systematic studies of how misinformation and fact-checking spread and compete on Twitter. Hoaxy captures public tweets that include links to articles from low-credibility and fact-checking sources. We perform k-core decomposition on a diffusion network obtained from two million retweets produced by several hundred thousand accounts over the six months before the election. As we move from the periphery to the core of the network, fact-checking nearly disappears, while social bots proliferate. The number of users in the main core reaches equilibrium around the time of the election, with limited churn and increasingly dense connections. We conclude by quantifying how effectively the network can be disrupted by penalizing the most central nodes. These findings provide a first look at the anatomy of a massive online misinformation diffusion network. PMID:29702657

  16. Anatomy of an online misinformation network.

    Science.gov (United States)

    Shao, Chengcheng; Hui, Pik-Mai; Wang, Lei; Jiang, Xinwen; Flammini, Alessandro; Menczer, Filippo; Ciampaglia, Giovanni Luca

    2018-01-01

    Massive amounts of fake news and conspiratorial content have spread over social media before and after the 2016 US Presidential Elections despite intense fact-checking efforts. How do the spread of misinformation and fact-checking compete? What are the structural and dynamic characteristics of the core of the misinformation diffusion network, and who are its main purveyors? How to reduce the overall amount of misinformation? To explore these questions we built Hoaxy, an open platform that enables large-scale, systematic studies of how misinformation and fact-checking spread and compete on Twitter. Hoaxy captures public tweets that include links to articles from low-credibility and fact-checking sources. We perform k-core decomposition on a diffusion network obtained from two million retweets produced by several hundred thousand accounts over the six months before the election. As we move from the periphery to the core of the network, fact-checking nearly disappears, while social bots proliferate. The number of users in the main core reaches equilibrium around the time of the election, with limited churn and increasingly dense connections. We conclude by quantifying how effectively the network can be disrupted by penalizing the most central nodes. These findings provide a first look at the anatomy of a massive online misinformation diffusion network.

  17. Optimizing online social networks for information propagation.

    Directory of Open Access Journals (Sweden)

    Duan-Bing Chen

    Full Text Available Online users nowadays are facing serious information overload problem. In recent years, recommender systems have been widely studied to help people find relevant information. Adaptive social recommendation is one of these systems in which the connections in the online social networks are optimized for the information propagation so that users can receive interesting news or stories from their leaders. Validation of such adaptive social recommendation methods in the literature assumes uniform distribution of users' activity frequency. In this paper, our empirical analysis shows that the distribution of online users' activity is actually heterogenous. Accordingly, we propose a more realistic multi-agent model in which users' activity frequency are drawn from a power-law distribution. We find that previous social recommendation methods lead to serious delay of information propagation since many users are connected to inactive leaders. To solve this problem, we design a new similarity measure which takes into account users' activity frequencies. With this similarity measure, the average delay is significantly shortened and the recommendation accuracy is largely improved.

  18. Optimizing online social networks for information propagation.

    Science.gov (United States)

    Chen, Duan-Bing; Wang, Guan-Nan; Zeng, An; Fu, Yan; Zhang, Yi-Cheng

    2014-01-01

    Online users nowadays are facing serious information overload problem. In recent years, recommender systems have been widely studied to help people find relevant information. Adaptive social recommendation is one of these systems in which the connections in the online social networks are optimized for the information propagation so that users can receive interesting news or stories from their leaders. Validation of such adaptive social recommendation methods in the literature assumes uniform distribution of users' activity frequency. In this paper, our empirical analysis shows that the distribution of online users' activity is actually heterogenous. Accordingly, we propose a more realistic multi-agent model in which users' activity frequency are drawn from a power-law distribution. We find that previous social recommendation methods lead to serious delay of information propagation since many users are connected to inactive leaders. To solve this problem, we design a new similarity measure which takes into account users' activity frequencies. With this similarity measure, the average delay is significantly shortened and the recommendation accuracy is largely improved.

  19. Online social networking issues within academia and pharmacy education.

    Science.gov (United States)

    Cain, Jeff

    2008-02-15

    Online social networking sites such as Facebook and MySpace are extremely popular as indicated by the numbers of members and visits to the sites. They allow students to connect with users with similar interests, build and maintain relationships with friends, and feel more connected with their campus. The foremost criticisms of online social networking are that students may open themselves to public scrutiny of their online personas and risk physical safety by revealing excessive personal information. This review outlines issues of online social networking in higher education by drawing upon articles in both the lay press and academic publications. New points for pharmacy educators to consider include the possible emergence of an "e-professionalism" concept; legal and ethical implications of using online postings in admission, discipline, and student safety decisions; how online personas may blend into professional life; and the responsibility for educating students about the risks of online social networking.

  20. Online social networking in people with psychosis: A systematic review.

    Science.gov (United States)

    Highton-Williamson, Elizabeth; Priebe, Stefan; Giacco, Domenico

    2015-02-01

    Online social networking might facilitate the establishment of social contacts for people with psychosis, who are often socially isolated by the symptoms and consequences of their disorder. We carried out a systematic review exploring available evidence on the use of online social networking in people with psychosis. The review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Included studies examined the use of the online social networking by people with an a priori diagnosis of psychosis (inclusive of bipolar disorder). Data from included studies were extracted and narratively synthesised. A total of 11 studies, published between 2005 and 2013, reported data on online social networking in people with psychosis. People with psychosis seem to spend more time in chat rooms or playing online games than control groups. The use of other online tools, such as Facebook or communication through e-mail, is lower or the same than controls. Online social networking was used by patients with psychosis for establishing new relationships, maintaining relationships/reconnecting with people and online peer support. Online social networking, in the form of forums or online chats, could play a role in strategies aimed at enhancing social networks and reduce the risk of isolation in this population. © The Author(s) 2014.

  1. Social networking in online support groups for health: how online social networking benefits patients.

    Science.gov (United States)

    Chung, Jae Eun

    2014-01-01

    An increasing number of online support groups (OSGs) have embraced the features of social networking. So far, little is known about how patients use and benefit from these features. By implementing the uses-and-gratifications framework, the author conducted an online survey with current users of OSGs to examine associations among motivation, use of specific features of OSG, and support outcomes. Findings suggest that OSG users make selective use of varied features depending on their needs, and that perceptions of receiving emotional and informational support are associated more with the use of some features than others. For example, those with strong motivation for social interaction use diverse features of OSG and make one-to-one connections with other users by friending. In contrast, those with strong motivation for information seeking limit their use primarily to discussion boards. Results also show that online social networking features, such as friending and sharing of personal stories on blogs, are helpful in satisfying the need for emotional support. The present study sheds light on online social networking features in the context of health-related OSGs and provides practical lessons on how to improve the capacity of OSGs to serve the needs of their users.

  2. Modeling online social networks based on preferential linking

    International Nuclear Information System (INIS)

    Hu Hai-Bo; Chen Jun; Guo Jin-Li

    2012-01-01

    We study the phenomena of preferential linking in a large-scale evolving online social network and find that the linear preference holds for preferential creation, preferential acceptance, and preferential attachment. Based on the linear preference, we propose an analyzable model, which illustrates the mechanism of network growth and reproduces the process of network evolution. Our simulations demonstrate that the degree distribution of the network produced by the model is in good agreement with that of the real network. This work provides a possible bridge between the micro-mechanisms of network growth and the macrostructures of online social networks

  3. Measuring structural similarity in large online networks.

    Science.gov (United States)

    Shi, Yongren; Macy, Michael

    2016-09-01

    Structural similarity based on bipartite graphs can be used to detect meaningful communities, but the networks have been tiny compared to massive online networks. Scalability is important in applications involving tens of millions of individuals with highly skewed degree distributions. Simulation analysis holding underlying similarity constant shows that two widely used measures - Jaccard index and cosine similarity - are biased by the distribution of out-degree in web-scale networks. However, an alternative measure, the Standardized Co-incident Ratio (SCR), is unbiased. We apply SCR to members of Congress, musical artists, and professional sports teams to show how massive co-following on Twitter can be used to map meaningful affiliations among cultural entities, even in the absence of direct connections to one another. Our results show how structural similarity can be used to map cultural alignments and demonstrate the potential usefulness of social media data in the study of culture, politics, and organizations across the social and behavioral sciences. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. Online Social Networks - Opportunities for Empowering Cancer Patients.

    Science.gov (United States)

    Mohammadzadeh, Zeinab; Davoodi, Somayeh; Ghazisaeidi, Marjan

    2016-01-01

    Online social network technologies have become important to health and apply in most health care areas. Particularly in cancer care, because it is a disease which involves many social aspects, online social networks can be very useful. Use of online social networks provides a suitable platform for cancer patients and families to present and share information about their medical conditions, address their educational needs, support decision making, and help to coping with their disease and improve their own outcomes. Like any other new technologies, online social networks, along with many benefits, have some negative effects such as violation of privacy and publication of incorrect information. However, if these effects are managed properly, they can empower patients to manage cancer through changing behavioral patterns and enhancing the quality of cancer patients lives This paper explains some application of online social networks in the cancer patient care process. It also covers advantages and disadvantages of related technologies.

  5. A last updating evolution model for online social networks

    Science.gov (United States)

    Bu, Zhan; Xia, Zhengyou; Wang, Jiandong; Zhang, Chengcui

    2013-05-01

    As information technology has advanced, people are turning to electronic media more frequently for communication, and social relationships are increasingly found on online channels. However, there is very limited knowledge about the actual evolution of the online social networks. In this paper, we propose and study a novel evolution network model with the new concept of “last updating time”, which exists in many real-life online social networks. The last updating evolution network model can maintain the robustness of scale-free networks and can improve the network reliance against intentional attacks. What is more, we also found that it has the “small-world effect”, which is the inherent property of most social networks. Simulation experiment based on this model show that the results and the real-life data are consistent, which means that our model is valid.

  6. Online and Offline Social Networks: Use of Social Networking Sites by Emerging Adults

    Science.gov (United States)

    Subrahmanyam, Kaveri; Reich, Stephanie M.; Waechter, Natalia; Espinoza, Guadalupe

    2008-01-01

    Social networking sites (e.g., MySpace and Facebook) are popular online communication forms among adolescents and emerging adults. Yet little is known about young people's activities on these sites and how their networks of "friends" relate to their other online (e.g., instant messaging) and offline networks. In this study, college students…

  7. VIOLIN: vaccine investigation and online information network.

    Science.gov (United States)

    Xiang, Zuoshuang; Todd, Thomas; Ku, Kim P; Kovacic, Bethany L; Larson, Charles B; Chen, Fang; Hodges, Andrew P; Tian, Yuying; Olenzek, Elizabeth A; Zhao, Boyang; Colby, Lesley A; Rush, Howard G; Gilsdorf, Janet R; Jourdian, George W; He, Yongqun

    2008-01-01

    Vaccines are among the most efficacious and cost-effective tools for reducing morbidity and mortality caused by infectious diseases. The vaccine investigation and online information network (VIOLIN) is a web-based central resource, allowing easy curation, comparison and analysis of vaccine-related research data across various human pathogens (e.g. Haemophilus influenzae, human immunodeficiency virus (HIV) and Plasmodium falciparum) of medical importance and across humans, other natural hosts and laboratory animals. Vaccine-related peer-reviewed literature data have been downloaded into the database from PubMed and are searchable through various literature search programs. Vaccine data are also annotated, edited and submitted to the database through a web-based interactive system that integrates efficient computational literature mining and accurate manual curation. Curated information includes general microbial pathogenesis and host protective immunity, vaccine preparation and characteristics, stimulated host responses after vaccination and protection efficacy after challenge. Vaccine-related pathogen and host genes are also annotated and available for searching through customized BLAST programs. All VIOLIN data are available for download in an eXtensible Markup Language (XML)-based data exchange format. VIOLIN is expected to become a centralized source of vaccine information and to provide investigators in basic and clinical sciences with curated data and bioinformatics tools for vaccine research and development. VIOLIN is publicly available at http://www.violinet.org.

  8. Academics and Social Networking Sites: Benefits, Problems and Tensions in Professional Engagement with Online Networking

    OpenAIRE

    Jordan, Katy; Weller, Martin

    2018-01-01

    The web has had a profound effect on the ways people interact, with online social networks arguably playing an important role in changing or augmenting how we connect with others. However, uptake of online social networking by the academic community varies, and needs to be understood. This paper presents an independent, novel analysis of a large-scale dataset published by Nature Publishing Group detailing the results of a survey about academics use of online social networking services. An ope...

  9. An information spreading model based on online social networks

    Science.gov (United States)

    Wang, Tao; He, Juanjuan; Wang, Xiaoxia

    2018-01-01

    Online social platforms are very popular in recent years. In addition to spreading information, users could review or collect information on online social platforms. According to the information spreading rules of online social network, a new information spreading model, namely IRCSS model, is proposed in this paper. It includes sharing mechanism, reviewing mechanism, collecting mechanism and stifling mechanism. Mean-field equations are derived to describe the dynamics of the IRCSS model. Moreover, the steady states of reviewers, collectors and stiflers and the effects of parameters on the peak values of reviewers, collectors and sharers are analyzed. Finally, numerical simulations are performed on different networks. Results show that collecting mechanism and reviewing mechanism, as well as the connectivity of the network, make information travel wider and faster, and compared to WS network and ER network, the speed of reviewing, sharing and collecting information is fastest on BA network.

  10. Emergence, evolution and scaling of online social networks.

    Science.gov (United States)

    Wang, Le-Zhi; Huang, Zi-Gang; Rong, Zhi-Hai; Wang, Xiao-Fan; Lai, Ying-Cheng

    2014-01-01

    Online social networks have become increasingly ubiquitous and understanding their structural, dynamical, and scaling properties not only is of fundamental interest but also has a broad range of applications. Such networks can be extremely dynamic, generated almost instantaneously by, for example, breaking-news items. We investigate a common class of online social networks, the user-user retweeting networks, by analyzing the empirical data collected from Sina Weibo (a massive twitter-like microblogging social network in China) with respect to the topic of the 2011 Japan earthquake. We uncover a number of algebraic scaling relations governing the growth and structure of the network and develop a probabilistic model that captures the basic dynamical features of the system. The model is capable of reproducing all the empirical results. Our analysis not only reveals the basic mechanisms underlying the dynamics of the retweeting networks, but also provides general insights into the control of information spreading on such networks.

  11. Emergence, evolution and scaling of online social networks.

    Directory of Open Access Journals (Sweden)

    Le-Zhi Wang

    Full Text Available Online social networks have become increasingly ubiquitous and understanding their structural, dynamical, and scaling properties not only is of fundamental interest but also has a broad range of applications. Such networks can be extremely dynamic, generated almost instantaneously by, for example, breaking-news items. We investigate a common class of online social networks, the user-user retweeting networks, by analyzing the empirical data collected from Sina Weibo (a massive twitter-like microblogging social network in China with respect to the topic of the 2011 Japan earthquake. We uncover a number of algebraic scaling relations governing the growth and structure of the network and develop a probabilistic model that captures the basic dynamical features of the system. The model is capable of reproducing all the empirical results. Our analysis not only reveals the basic mechanisms underlying the dynamics of the retweeting networks, but also provides general insights into the control of information spreading on such networks.

  12. Stochastic Online Learning in Dynamic Networks under Unknown Models

    Science.gov (United States)

    2016-08-02

    The key is to develop online learning strategies at each individual node. Specifically, through local information exchange with its neighbors, each...infinitely repeated game with incomplete information and developed a dynamic pricing strategy referred to as Competitive and Cooperative Demand Learning...Stochastic Online Learning in Dynamic Networks under Unknown Models This research aims to develop fundamental theories and practical algorithms for

  13. Exploring Self-Disclosure in Online Social Networks

    Science.gov (United States)

    Velasco-Martin, Javier

    2013-01-01

    This project explores how experienced adult users of social media disclose personal information over online social networks (OSN). This work introduces a four-dimensional model to serve as a foundational framework for the study of online self-disclosure (OSD); these four dimensions are personal, social, technological and contextual, and support…

  14. Adolescents' and Emerging Adults' Social Networking Online: Homophily or Diversity?

    Science.gov (United States)

    Mazur, Elizabeth; Richards, Lacey

    2011-01-01

    More than half of all online American adolescents and emerging adults have created personal profiles for social networking on the Internet. Does homophily in their offline friendships extend online? Drawing mainly on research of face-to-face friendship, we collected data from the public spaces, called "walls," of 129 young Americans ages 16 to 19…

  15. Blessed Oblivion? Knowledge and Metacognitive Accuracy in Online Social Networks

    Science.gov (United States)

    Moll, Ricarda; Pieschl, Stephanie; Bromme, Rainer

    2015-01-01

    In order to reap the social gratifications of Online Social Networks (OSNs), users often disclose self-related information, making them potentially vulnerable to their online audiences. We give a brief overview of our theoretical ideas and empirical research about additional cognitive and metacognitive factors relevant for the perception of risk…

  16. Methods of Profile Cloning Detection in Online Social Networks

    Directory of Open Access Journals (Sweden)

    Zabielski Michał

    2016-01-01

    Full Text Available With the arrival of online social networks, the importance of privacy on the Internet has increased dramatically. Thus, it is important to develop mechanisms that will prevent our hidden personal data from unauthorized access and use. In this paper an attempt was made to present a concept of profile cloning detection in Online Social Networks (OSN using Graph and Networks Theory. By analysing structural similarity of network and value of attributes of user personal profile, we will be able to search for attackers which steal our identity.

  17. Online networks, social interaction and segregation: An evolutionary approach

    OpenAIRE

    Antoci, Angelo; Sabatini, Fabio

    2018-01-01

    There is growing evidence that face-to-face interaction is declining in many countries, exacerbating the phenomenon of social isolation. On the other hand, social interaction through online networking sites is steeply rising. To analyze these societal dynamics, we have built an evolutionary game model in which agents can choose between three strategies of social participation: 1) interaction via both online social networks and face-to-face encounters; 2) interaction by exclusive means of face...

  18. Essential elements of online information networks on invasive alien species

    Science.gov (United States)

    Simpson, A.; Sellers, E.; Grosse, A.; Xie, Y.

    2006-01-01

    In order to be effective, information must be placed in the proper context and organized in a manner that is logical and (preferably) standardized. Recently, invasive alien species (IAS) scientists have begun to create online networks to share their information concerning IAS prevention and control. At a special networking session at the Beijing International Symposium on Biological Invasions, an online Eastern Asia-North American IAS Information Network (EA-NA Network) was proposed. To prepare for the development of this network, and to provide models for other regional collaborations, we compare four examples of global, regional, and national online IAS information networks: the Global Invasive Species Information Network, the Invasives Information Network of the Inter-American Biodiversity Information Network, the Chinese Species Information System, and the Invasive Species Information Node of the US National Biological Information Infrastructure. We conclude that IAS networks require a common goal, dedicated leaders, effective communication, and broad endorsement, in order to obtain sustainable, long-term funding and long-term stability. They need to start small, use the experience of other networks, partner with others, and showcase benefits. Global integration and synergy among invasive species networks will succeed with contributions from both the top-down and the bottom-up. ?? 2006 Springer.

  19. The effects of online social networks on tacit knowledge transmission

    Science.gov (United States)

    Zhu, Hong-Miao; Zhang, Sheng-Tai; Jin, Zhen

    2016-01-01

    Due to the popular use of online social networks in today's world, how to propagate employees' tacit knowledge via online social networks has attracted managers' attention, which is critical to enhance the competitiveness of firms. In this paper, we propose a tacit knowledge transmission model on networks with even mixing based on the propagation property of tacit knowledge and the application of online social networks. We consider two routes of transmission, which are contact through online social networks and face-to-face physical contact, and derive the threshold that governs whether or not a kind of tacit knowledge can be shared in an organization with few initial employees who have acquired it. The impact of the degree distribution of the users' contact network on the transmission is investigated analytically. Some numerical simulations are presented to support the theoretical results. We perform the sensitivity analysis of the threshold in terms of the propagation parameters and confirm that online social networks contribute significantly to enhancing the transmission of tacit knowledge among employees.

  20. Spreading in online social networks: the role of social reinforcement.

    Science.gov (United States)

    Zheng, Muhua; Lü, Linyuan; Zhao, Ming

    2013-07-01

    Some epidemic spreading models are usually applied to analyze the propagation of opinions or news. However, the dynamics of epidemic spreading and information or behavior spreading are essentially different in many aspects. Centola's experiments [Science 329, 1194 (2010)] on behavior spreading in online social networks showed that the spreading is faster and broader in regular networks than in random networks. This result contradicts with the former understanding that random networks are preferable for spreading than regular networks. To describe the spreading in online social networks, a unknown-known-approved-exhausted four-status model was proposed, which emphasizes the effect of social reinforcement and assumes that the redundant signals can improve the probability of approval (i.e., the spreading rate). Performing the model on regular and random networks, it is found that our model can well explain the results of Centola's experiments on behavior spreading and some former studies on information spreading in different parameter space. The effects of average degree and network size on behavior spreading process are further analyzed. The results again show the importance of social reinforcement and are accordant with Centola's anticipation that increasing the network size or decreasing the average degree will enlarge the difference of the density of final approved nodes between regular and random networks. Our work complements the former studies on spreading dynamics, especially the spreading in online social networks where the information usually requires individuals' confirmations before being transmitted to others.

  1. Integrated Networks: National and International Online Experiences

    Directory of Open Access Journals (Sweden)

    Osvaldo Muniz-Solari

    2009-02-01

    Full Text Available There is an increasing impression among online geography educators that interaction can be developed based on specific teaching and learning methods. The authors developed a practical research study to investigate this issue. The study was based on advanced graduate courses in geography at Beijing Normal University and Texas State University. International interaction was complemented by online collaboration among the US local group. Both synchronous and asynchronous communication systems were used, which spanned two platforms. Results of this experience indicate that teaching and learning methods must be enhanced by a flexible online learning model and extensive organizational support in order to increase interaction and reach a certain level of cooperation.

  2. Academics and Social Networking Sites: Benefits, Problems and Tensions in Professional Engagement with Online Networking

    Science.gov (United States)

    Jordan, Katy; Weller, Martin

    2018-01-01

    The web has had a profound effect on the ways people interact, with online social networks arguably playing an important role in changing or augmenting how we connect with others. However, uptake of online social networking by the academic community varies, and needs to be understood. This paper presents an independent, novel analysis of a…

  3. Studies on the population dynamics of a rumor-spreading model in online social networks

    Science.gov (United States)

    Dong, Suyalatu; Fan, Feng-Hua; Huang, Yong-Chang

    2018-02-01

    This paper sets up a rumor spreading model in online social networks based on the European fox rabies SIR model. The model considers the impact of changing number of online social network users, combines the transmission dynamics to set up a population dynamics of rumor spreading model in online social networks. Simulation is carried out on online social network, and results show that the new rumor spreading model is in accordance with the real propagation characteristics in online social networks.

  4. Blending Formal and Informal Learning Networks for Online Learning

    Science.gov (United States)

    Czerkawski, Betül C.

    2016-01-01

    With the emergence of social software and the advance of web-based technologies, online learning networks provide invaluable opportunities for learning, whether formal or informal. Unlike top-down, instructor-centered, and carefully planned formal learning settings, informal learning networks offer more bottom-up, student-centered participatory…

  5. Environmental Learning in Online Social Networks: Adopting Environmentally Responsible Behaviors

    Science.gov (United States)

    Robelia, Beth A.; Greenhow, Christine; Burton, Lisa

    2011-01-01

    Online social networks are increasingly important information and communication tools for young people and for the environmental movement. Networks may provide the motivation for young adults to increase environmental behaviors by increasing their knowledge of environmental issues and of the specific actions they can take to reduce greenhouse gas…

  6. How Will Online Affiliate Marketing Networks Impact Search Engine Rankings?

    NARCIS (Netherlands)

    D. Janssen (David); H.W.G.M. van Heck (Eric)

    2007-01-01

    textabstractIn online affiliate marketing networks advertising web sites offer their affiliates revenues based on provided web site traffic and associated leads and sales. Advertising web sites can have a network of thousands of affiliates providing them with web site traffic through hyperlinks on

  7. Effect of online social networking on employee productivity

    OpenAIRE

    A. Ferreira; T. du Plessis

    2009-01-01

    The popularity of social networking sites is relatively recent and the effect of online social networking (OSN) on employee productivity has not received much scholarly attention. The reason most likely lies in the social nature of social networking sites and OSN, which is assumed to have a negative effect on employee productivity and not bear organisational benefit. This reseach investigated recent Internet developments as seen in the social Web and specifically investigated the effect of OS...

  8. Friend or Foe? Fake Profile Identification in Online Social Networks

    OpenAIRE

    Fire, Michael; Kagan, Dima; Elyashar, Aviad; Elovici, Yuval

    2013-01-01

    The amount of personal information unwillingly exposed by users on online social networks is staggering, as shown in recent research. Moreover, recent reports indicate that these networks are infested with tens of millions of fake users profiles, which may jeopardize the users' security and privacy. To identify fake users in such networks and to improve users' security and privacy, we developed the Social Privacy Protector software for Facebook. This software contains three protection layers,...

  9. Characterizing interactions in online social networks during exceptional events

    Science.gov (United States)

    Omodei, Elisa; De Domenico, Manlio; Arenas, Alex

    2015-08-01

    Nowadays, millions of people interact on a daily basis on online social media like Facebook and Twitter, where they share and discuss information about a wide variety of topics. In this paper, we focus on a specific online social network, Twitter, and we analyze multiple datasets each one consisting of individuals' online activity before, during and after an exceptional event in terms of volume of the communications registered. We consider important events that occurred in different arenas that range from policy to culture or science. For each dataset, the users' online activities are modeled by a multilayer network in which each layer conveys a different kind of interaction, specifically: retweeting, mentioning and replying. This representation allows us to unveil that these distinct types of interaction produce networks with different statistical properties, in particular concerning the degree distribution and the clustering structure. These results suggests that models of online activity cannot discard the information carried by this multilayer representation of the system, and should account for the different processes generated by the different kinds of interactions. Secondly, our analysis unveils the presence of statistical regularities among the different events, suggesting that the non-trivial topological patterns that we observe may represent universal features of the social dynamics on online social networks during exceptional events.

  10. Exploring online evolution of network stacks

    OpenAIRE

    Imai, Pierre

    2013-01-01

    Network stacks today follow a one-size-fits-all philosophy. They are mostly kept unmodified due to often prohibitive costs of engineering, deploying and administrating customisation of the networking software, with the Internet stack architecture still largely being based on designs and assumptions made for the ARPANET 40 years ago. We venture that heterogeneous and rapidly changing networks of the future require, in order to be successful, run-time self-adaptation mechanisms at different tim...

  11. Competition between global and local online social networks

    Science.gov (United States)

    Kleineberg, Kaj-Kolja; Boguñá, Marián

    2016-04-01

    The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

  12. Competition between global and local online social networks.

    Science.gov (United States)

    Kleineberg, Kaj-Kolja; Boguñá, Marián

    2016-04-27

    The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

  13. Sentiment Polarization and Balance among Users in Online Social Networks

    DEFF Research Database (Denmark)

    Hillmann, Robert; Trier, Matthias

    2012-01-01

    Communication within online social network applications enables users to express and share sentiments electronically. Existing studies examined the existence or distribution of sentiments in online communication at a general level or in small-observed groups. Our paper extends this research...... by analyzing sentiment exchange within social networks from an ego-network perspective. We draw from research on social influence and social attachment to develop theories of node polarization, balance effects and sentiment mirroring within communication dyads. Our empirical analysis covers a multitude...... of social networks in which the sentiment valence of all messages was determined. Subsequently we studied ego-networks of focal actors (ego) and their immediate contacts. Results support our theories and indicate that actors develop polarized sentiments towards individual peers but keep sentiment in balance...

  14. Incorporating profile information in community detection for online social networks

    Science.gov (United States)

    Fan, W.; Yeung, K. H.

    2014-07-01

    Community structure is an important feature in the study of complex networks. It is because nodes of the same community may have similar properties. In this paper we extend two popular community detection methods to partition online social networks. In our extended methods, the profile information of users is used for partitioning. We apply the extended methods in several sample networks of Facebook. Compared with the original methods, the community structures we obtain have higher modularity. Our results indicate that users' profile information is consistent with the community structure of their friendship network to some extent. To the best of our knowledge, this paper is the first to discuss how profile information can be used to improve community detection in online social networks.

  15. Marketing the Academic Library with Online Social Network Advertising

    OpenAIRE

    CHan, Christopher

    2012-01-01

    Facebook is now a ubiquitous part of the lives of many university students across the world. The libraries that serve them now have an opportunity to leverage this online social network to promote their services and resources. However, the effectiveness of a library’s efforts in this area will depend greatly on the number of connections it can make between its users and its Facebook presence. Building on a previous investigation that suggested online advertising might be a cost-effective way ...

  16. Exploration of Online Culture Through Network Analysis of Wikipedia.

    Science.gov (United States)

    Park, Sung Joo; Kim, Jong Woo; Lee, Hong Joo; Park, Hyunjung; Han, Deugcheon; Gloor, Peter

    2015-11-01

    Understanding online culture is becoming crucial in the global and connected world. Contrary to conventional attitudinal surveys used in cultural research, this study uses the approach of directly observing culture-specific behavior that emerges from online collaboration on the Internet. The editing data of Wikipedia were analyzed in 12 languages. Distinctive cultural dimensions were identified, including collectivism, extraversion, boldness, and egalitarianism. Using network analysis, the language-framed cultural factors were extracted as an emergent phenomenon in the virtual world.

  17. Entrepreneurial Idea Identification through Online Social Networks

    Science.gov (United States)

    Lang, Matthew C.

    2010-01-01

    The increasing use of social network websites may signal a change in the way the next generation of entrepreneurs identify entrepreneurial ideas. An important part of the entrepreneurship literature emphasizes how vital the use of social networks is to entrepreneurial idea identification, opportunity recognition, and ultimately new venture…

  18. Psychodynamic Factors Behind Online Social Networking and its Excessive Use.

    Science.gov (United States)

    Li, Thomas Cheuk Wing

    2016-03-01

    This article discusses the psychodynamic factors behind the popularity of one form of Internet activity, online social networking (SN). It views online SN as an extension of the social self, organized in a way that is more controllable than real life relating. The SN platforms reward its users with reassuring surfaces and novel self-object experiences while at the same time induces much anxiety. The addictive quality of online SN is understood in the context of collapse of dialectical space and the defensive use of this technology.

  19. A Study of Malware Propagation via Online Social Networking

    Science.gov (United States)

    Faghani, Mohammad Reza; Nguyen, Uyen Trang

    The popularity of online social networks (OSNs) have attracted malware creators who would use OSNs as a platform to propagate automated worms from one user's computer to another's. On the other hand, the topic of malware propagation in OSNs has only been investigated recently. In this chapter, we discuss recent advances on the topic of malware propagation by way of online social networking. In particular, we present three malware propagation techniques in OSNs, namely cross site scripting (XSS), Trojan and clickjacking types, and their characteristics via analytical models and simulations.

  20. Detecting Friendship Within Dynamic Online Interaction Networks

    OpenAIRE

    Merritt, Sears; Jacobs, Abigail Z.; Mason, Winter; Clauset, Aaron

    2013-01-01

    In many complex social systems, the timing and frequency of interactions between individuals are observable but friendship ties are hidden. Recovering these hidden ties, particularly for casual users who are relatively less active, would enable a wide variety of friendship-aware applications in domains where labeled data are often unavailable, including online advertising and national security. Here, we investigate the accuracy of multiple statistical features, based either purely on temporal...

  1. Interface Prostheses With Classifier-Feedback-Based User Training.

    Science.gov (United States)

    Fang, Yinfeng; Zhou, Dalin; Li, Kairu; Liu, Honghai

    2017-11-01

    It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well as the centroids of the training samples, whose dimensionality is reduced to minimal number by dimension reduction. Clustering feedback provides a criterion that guides users to adjust motion gestures and muscle contraction forces intentionally. The experiment results have demonstrated that hand motion recognition accuracy increases steadily along the progress of the clustering-feedback-based user training, while conventional classifier-feedback methods, i.e., label feedback, hardly achieve any improvement. The result concludes that the use of proper classifier feedback can accelerate the process of user training, and implies prosperous future for the amputees with limited or no experience in pattern-recognition-based prosthetic device manipulation.It is evident that user training significantly affects performance of pattern-recognition-based myoelectric prosthetic device control. Despite plausible classification accuracy on offline datasets, online accuracy usually suffers from the changes in physiological conditions and electrode displacement. The user ability in generating consistent electromyographic (EMG) patterns can be enhanced via proper user training strategies in order to improve online performance. This study proposes a clustering-feedback strategy that provides real-time feedback to users by means of a visualized online EMG signal input as well

  2. Modeling the Propagation of Trojan Malware in Online Social Networks

    OpenAIRE

    Faghani, Mohammad Reza; Nugyen, Uyen Trang

    2017-01-01

    The popularity and widespread usage of online social networks (OSN) have attracted cyber criminals who have used OSNs as a platform to spread malware. Among different types of malware in OSNs, Trojan is the most popular type with hundreds of attacks on OSN users in the past few years. Trojans infecting a user's computer have the ability to steal confidential information, install ransomware and infect other computers in the network. Therefore, it is important to understand propagation dynamics...

  3. Login and Networking Services for Online Multiplayer Games

    OpenAIRE

    Peachi Muthu, Chithra

    2015-01-01

    The aim of the thesis was to study login and networking services for online multiplayer games using the unity tool. In the thesis, the authentication, communication and networking protocols supported in the unity game development tool were studied and experimented. And an analysis of the possibility to use the SIP protocol for the login services was done. A game development team from a game company, Vulpine Games Oy, was identified with the help of a lecturer in Metropolia. With the team the ...

  4. Private Sharing of User Location over Online Social Networks

    OpenAIRE

    Freudiger, Julien; Neu, Raoul; Hubaux, Jean-Pierre

    2010-01-01

    Online social networks increasingly allow mobile users to share their location with their friends. Much to the detriment of users’ privacy, this also means that social network operators collect users’ lo- cation. Similarly, third parties can learn users’ location from localization and location visualization services. Ideally, third-parties should not be given complete access to users’ location. To protect location privacy, we design and implement a platform-independent solution for users to s...

  5. On-line learning in radial basis functions networks

    OpenAIRE

    Freeman, Jason; Saad, David

    1997-01-01

    An analytic investigation of the average case learning and generalization properties of Radial Basis Function Networks (RBFs) is presented, utilising on-line gradient descent as the learning rule. The analytic method employed allows both the calculation of generalization error and the examination of the internal dynamics of the network. The generalization error and internal dynamics are then used to examine the role of the learning rate and the specialization of the hidden units, which gives ...

  6. How Will Online Affiliate Marketing Networks Impact Search Engine Rankings?

    OpenAIRE

    Janssen, David; Heck, Eric

    2007-01-01

    textabstractIn online affiliate marketing networks advertising web sites offer their affiliates revenues based on provided web site traffic and associated leads and sales. Advertising web sites can have a network of thousands of affiliates providing them with web site traffic through hyperlinks on their web sites. Search engines such as Google, MSN, and Yahoo, consider hyperlinks as a proof of quality and/or reliability of the linked web sites, and therefore use them to determine the relevanc...

  7. Understanding the impact of online social networks on disruptive innovation

    NARCIS (Netherlands)

    Cizel, A; Boonstra, A.; Langley, D.J.; Tan, C.W.

    2013-01-01

    In this paper we explore the state of current knowledge about online social networks (OSNs), and their role in precipitating changes in existing market structures. We do so by reviewing more than 30 recent papers from top-ranked journals in the relevant fields of study. We begin by providing a

  8. Pharmacists on Facebook: online social networking and the profession.

    Science.gov (United States)

    Mattingly, T Joseph; Cain, Jeff; Fink, Joseph L

    2010-01-01

    To provide a brief history of Facebook and online social networking and discuss how it has contributed and can contribute in the future to a paradigm change in social communications. When student pharmacists complete school and enter practice, they encounter enhanced expectations to act appropriately and professionally. Facebook expands the dilemma of separating private and public life--a challenge for individuals in all professions. From the standpoint of a professional association, Facebook provides a tremendous opportunity to reach out to members in an unprecedented way. Pharmacy organizations are beginning to use these new tools to increase communication and dissemination of information. The popularity of Facebook has brought the issue of online social networking to the forefront of professional and organizational discussions. The issues of privacy, identity protection, and e-professionalism are likely to reappear as pharmacists and student pharmacists continue to communicate via online networks. The potential exists for organizations to harness this organizational and communication power for their own interests. Further study is needed regarding the interaction between online social networking applications and the profession of pharmacy.

  9. User-friendly matching protocol for online social networks

    NARCIS (Netherlands)

    Tang, Qiang

    2010-01-01

    In this paper, we outline a privacy-preserving matching protocol for OSN (online social network) users to find their potential friends. With the proposed protocol, a logged-in user can match her profile with that of an off-line stranger, while both profiles are maximally protected. Our solution

  10. ODIN. Online Database Information Network: ODIN Policy & Procedure Manual.

    Science.gov (United States)

    Townley, Charles T.; And Others

    Policies and procedures are outlined for the Online Database Information Network (ODIN), a cooperative of libraries in south-central Pennsylvania, which was organized to improve library services through technology. The first section covers organization and goals, members, and responsibilities of the administrative council and libraries. Patrons…

  11. Leaders or Brokers? Potential Influencers in Online Parliamentary Networks

    NARCIS (Netherlands)

    Esteve Del Valle, Marc; Borge Bravo, Rosa

    2017-01-01

    The use of social media by parliamentarians is opening up a new communication arena. In Catalonia, where 85 percent of parliamentarians have a Twitter account, two questions emerge from this new social phenomenon. First, who are the opinion leaders of the parliamentarians’ online political networks,

  12. Competitive diffusion in online social networks with heterogeneous users

    Science.gov (United States)

    Li, Pei; He, Su; Wang, Hui; Zhang, Xin

    2014-06-01

    Online social networks have attracted increasing attention since they provide various approaches for hundreds of millions of people to stay connected with their friends. However, most research on diffusion dynamics in epidemiology cannot be applied directly to characterize online social networks, where users are heterogeneous and may act differently according to their standpoints. In this paper, we propose models to characterize the competitive diffusion in online social networks with heterogeneous users. We classify messages into two types (i.e., positive and negative) and users into three types (i.e., positive, negative and neutral). We estimate the positive (negative) influence for a user generating a given type message, which is the number of times that positive (negative) messages are processed (i.e., read) incurred by this action. We then consider the diffusion threshold, above which the corresponding influence will approach infinity, and the effect threshold, above which the unexpected influence of generating a message will exceed the expected one. We verify all these results by simulations, which show the analysis results are perfectly consistent with the simulation results. These results are of importance in understanding the diffusion dynamics in online social networks, and also critical for advertisers in viral marketing where there are fans, haters and neutrals.

  13. Online Networks as Societies : User Behaviors and Contribution Incentives

    NARCIS (Netherlands)

    Jia, L.

    2013-01-01

    Online networks like email, Facebook, LinkedIn, Wikipedia, eBay, and BitTorrent-like Peer-to-Peer (P2P) systems have become popular and powerful infrastructures for communication. They involve potentially large numbers of humans with their collective inputs and decisions, and they often rely on the

  14. Web Sites for Young Children: Gateway to Online Social Networking?

    Science.gov (United States)

    Bauman, Sheri; Tatum, Tanisha

    2009-01-01

    Traffic on Web sites for young children (ages 3-12) has increased exponentially in recent years. Advocates proclaim that they are safe introductions to the Internet and online social networking and teach essential 21st-century skills. Critics note developmental concerns. In this article, we provide basic information about Web sites for young…

  15. On-line plant-wide monitoring using neural networks

    International Nuclear Information System (INIS)

    Turkcan, E.; Ciftcioglu, O.; Eryurek, E.; Upadhyaya, B.R.

    1992-06-01

    The on-line signal analysis system designed for a multi-level mode operation using neural networks is described. The system is capable of monitoring the plant states by tracking different number of signals up to 32 simultaneously. The data used for this study were acquired from the Borssele Nuclear Power Plant (PWR type), and using the on-line monitoring system. An on-line plant-wide monitoring study using a multilayer neural network model is discussed in this paper. The back-propagation neural network algorithm is used for training the network. The technique assumes that each physical state of the power plant can be represented by a unique pattern of instrument readings which can be related to the condition of the plant. When disturbance occurs, the sensor readings undergo a transient, and form a different set of patterns which represent the new operational status. Diagnosing these patterns can be helpful in identifying this new state of the power plant. To this end, plant-wide monitoring with neutral networks is one of the new techniques in real-time applications. (author). 9 refs.; 5 figs

  16. Online Social Networks and the New Organizational Spaces

    Directory of Open Access Journals (Sweden)

    Cintia Rodrigues de Oliveira Medeiros

    2013-04-01

    Full Text Available We analyzed the ‘virtuality’ of the social space and the boundaries of organizations from the emergence and dissemination of online social networking. The purpose is to identify how the use of social networks by 10 Brazilian companies enables the redefinition and expansion of organizational space. For the analysis of the data, we used the theory of social space of Lefebvre (2004, which defines three moments of space social production: the imagined space, the lived space and the perceived space. The methodological qualitative approach is done by document analysis from the websites of the companies. We show that the organizational space has new contours with the adoption of online social networks and we analyzed four spatial metaphors: the square, the museum, the temple and the market.

  17. HIV/AIDS, social capital, and online social networks.

    Science.gov (United States)

    Drushel, Bruce E

    2013-01-01

    The prospects for online social networks as sites of information-gathering and affiliation for persons with AIDS and others concerned about HIV/AIDS not only represent the latest development in a trend toward circumventing traditional media and official information sources, but also may offer hope for a revitalization of HIV/AIDS discourse in the public sphere. This article provides an overview of three decades of information-seeking on the pandemic and its social and personal implications, as well as case studies of three examples of social networking surrounding HIV/AIDS. It finds preliminary evidence of the formation of strong and weak ties as described in Social Network Theory and suggests that the online accumulation of social capital by opinion leaders could facilitate dissemination of messages on HIV/AIDS awareness and testing.

  18. Virtual Social Networks Online and Mobile Systems

    Directory of Open Access Journals (Sweden)

    Maytham Safar

    2009-01-01

    Full Text Available Location-based applications are one of the most anticipated new segments of the mobile industry. These new applications are enabled by GPS-equipped phones (e.g., emergency applications, buddy finders, games, location-based advertising, etc.. These services are designed to give consumers instant access to personalized, local content of their immediate location. Some applications couple LBS with notification services, automatically alerting users when they are close to a pre-selected destination. With the advances in the Internet and communications/mobile technology, it became vital to analyze the effect of such technologies on human communications. This work studies how humans can construct social networks as a method for group communications using the available technologies. We constructed and analyzed a friends network using different parameters. The parameters that were calculated to analyze the network are the distribution sequence, characteristic path length, clustering coefficient and centrality measures. In addition, we built a PDA application that implements the concept of LBS using two system modules. In the first module, we have developed an application for entertainment purpose; an application program which enables end users to send their birth year and get their horoscope in return. The second part of the project was, to build an application, which helps people to stay in touch with their friends and family members (Find Friend. It helps users to find which of their buddies are within the same area they are in.

  19. Identifying online user reputation of user-object bipartite networks

    Science.gov (United States)

    Liu, Xiao-Lu; Liu, Jian-Guo; Yang, Kai; Guo, Qiang; Han, Jing-Ti

    2017-02-01

    Identifying online user reputation based on the rating information of the user-object bipartite networks is important for understanding online user collective behaviors. Based on the Bayesian analysis, we present a parameter-free algorithm for ranking online user reputation, where the user reputation is calculated based on the probability that their ratings are consistent with the main part of all user opinions. The experimental results show that the AUC values of the presented algorithm could reach 0.8929 and 0.8483 for the MovieLens and Netflix data sets, respectively, which is better than the results generated by the CR and IARR methods. Furthermore, the experimental results for different user groups indicate that the presented algorithm outperforms the iterative ranking methods in both ranking accuracy and computation complexity. Moreover, the results for the synthetic networks show that the computation complexity of the presented algorithm is a linear function of the network size, which suggests that the presented algorithm is very effective and efficient for the large scale dynamic online systems.

  20. Cognitive Benefits of Online Social Networking for Healthy Older Adults.

    Science.gov (United States)

    Myhre, Janelle W; Mehl, Matthias R; Glisky, Elizabeth L

    2017-09-01

    Research suggests that older adults who remain socially active and cognitively engaged have better cognitive function than those who are isolated and disengaged. This study examined the efficacy of learning and using an online social networking website, Facebook.com, as an intervention to maintain or enhance cognitive function in older adults. Forty-one older adults were assigned to learn and use Facebook (n = 14) or an online diary website (active control, n = 13) for 8 weeks or placed on a waitlist (n = 14). Outcome measures included neuropsychological tests of executive functions, memory, and processing speed and self-report questionnaires about social engagement. The Facebook group showed a significant increase in a composite measure of updating, an executive function factor associated with complex working memory tasks, compared to no significant change in the control groups. Other measures of cognitive function and social support showed no differential improvement in the Facebook group. Learning and using an online social networking site may provide specific benefits for complex working memory in a group of healthy older adults. This may reflect the particular cognitive demands associated with online social networking and/or the benefits of social engagement more generally. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  1. Privacy in Online Social Networking Sites

    OpenAIRE

    M.Ida Evones

    2015-01-01

    There are more than 192 act ive social networking websites. Bringing every kind of social group together in one place and letting them interact is really a big thing indeed .Huge amount of information process in the sites each day, end up making it vulnerable to attack. There is no systematic framework taking into account the importance of privacy. Increased privacy settings don’t always guarantee privacy when there is a loop hole in the applications. Lack of user education results is over sh...

  2. Leaking privacy and shadow profiles in online social networks.

    Science.gov (United States)

    Garcia, David

    2017-08-01

    Social interaction and data integration in the digital society can affect the control that individuals have on their privacy. Social networking sites can access data from other services, including user contact lists where nonusers are listed too. Although most research on online privacy has focused on inference of personal information of users, this data integration poses the question of whether it is possible to predict personal information of nonusers. This article tests the shadow profile hypothesis, which postulates that the data given by the users of an online service predict personal information of nonusers. Using data from a disappeared social networking site, we perform a historical audit to evaluate whether personal data of nonusers could have been predicted with the personal data and contact lists shared by the users of the site. We analyze personal information of sexual orientation and relationship status, which follow regular mixing patterns in the social network. Going back in time over the growth of the network, we measure predictor performance as a function of network size and tendency of users to disclose their contact lists. This article presents robust evidence supporting the shadow profile hypothesis and reveals a multiplicative effect of network size and disclosure tendencies that accelerates the performance of predictors. These results call for new privacy paradigms that take into account the fact that individual privacy decisions do not happen in isolation and are mediated by the decisions of others.

  3. Social networking and online recruiting for HIV research: ethical challenges.

    Science.gov (United States)

    Curtis, Brenda L

    2014-02-01

    Social networking sites and online advertising organizations provide HIV/AIDS researchers access to target populations, often reaching difficult-to-reach populations. However, this benefit to researchers raises many issues for the protections of prospective research participants. Traditional recruitment procedures have involved straightforward transactions between the researchers and prospective participants; online recruitment is a more complex and indirect form of communication involving many parties engaged in the collecting, aggregating, and storing of research participant data. Thus, increased access to online data has challenged the adequacy of current and established procedures for participants' protections, such as informed consent and privacy/confidentiality. Internet-based HIV/AIDS research recruitment and its ethical challenges are described, and research participant safeguards and best practices are outlined.

  4. Social Networking and Online Recruiting for HIV Research: Ethical Challenges

    Science.gov (United States)

    Curtis, Brenda L.

    2015-01-01

    Social networking sites and online advertising organizations provide HIV/AIDS researchers access to target populations, often reaching difficult-to-reach populations. However, this benefit to researchers raises many issues for the protections of prospective research participants. Traditional recruitment procedures have involved straightforward transactions between the researchers and prospective participants; online recruitment is a more complex and indirect form of communication involving many parties engaged in the collecting, aggregating, and storing of research participant data. Thus, increased access to online data has challenged the adequacy of current and established procedures for participants’ protections, such as informed consent and privacy/confidentiality. Internet-based HIV/AIDS research recruitment and its ethical challenges are described, and research participant safeguards and best practices are outlined. PMID:24572084

  5. Information filtering in evolving online networks

    Science.gov (United States)

    Chen, Bo-Lun; Li, Fen-Fen; Zhang, Yong-Jun; Ma, Jia-Lin

    2018-02-01

    Recommender systems use the records of users' activities and profiles of both users and products to predict users' preferences in the future. Considerable works towards recommendation algorithms have been published to solve the problems such as accuracy, diversity, congestion, cold-start, novelty, coverage and so on. However, most of these research did not consider the temporal effects of the information included in the users' historical data. For example, the segmentation of the training set and test set was completely random, which was entirely different from the real scenario in recommender systems. More seriously, all the objects are treated as the same, regardless of the new, the popular or obsoleted products, so do the users. These data processing methods always lose useful information and mislead the understanding of the system's state. In this paper, we detailed analyzed the difference of the network structure between the traditional random division method and the temporal division method on two benchmark data sets, Netflix and MovieLens. Then three classical recommendation algorithms, Global Ranking method, Collaborative Filtering and Mass Diffusion method, were employed. The results show that all these algorithms became worse in all four key indicators, ranking score, precision, popularity and diversity, in the temporal scenario. Finally, we design a new recommendation algorithm based on both users' and objects' first appearance time in the system. Experimental results showed that the new algorithm can greatly improve the accuracy and other metrics.

  6. The Dynamics of Protest Recruitment through an Online Network

    Science.gov (United States)

    González-Bailón, Sandra; Borge-Holthoefer, Javier; Rivero, Alejandro; Moreno, Yamir

    2011-12-01

    The recent wave of mobilizations in the Arab world and across Western countries has generated much discussion on how digital media is connected to the diffusion of protests. We examine that connection using data from the surge of mobilizations that took place in Spain in May 2011. We study recruitment patterns in the Twitter network and find evidence of social influence and complex contagion. We identify the network position of early participants (i.e. the leaders of the recruitment process) and of the users who acted as seeds of message cascades (i.e. the spreaders of information). We find that early participants cannot be characterized by a typical topological position but spreaders tend to be more central in the network. These findings shed light on the connection between online networks, social contagion, and collective dynamics, and offer an empirical test to the recruitment mechanisms theorized in formal models of collective action.

  7. Online social networking and the experience of cyber-bullying.

    Science.gov (United States)

    O'Dea, Bridianne; Campbell, Andrew

    2012-01-01

    Online social networking sites (SNS) are popular social tools used amongst adolescents and account for much of their daily internet activity. Recently, these sites have presented opportunities for youth to experience cyber-bullying. Often resulting in psychological distress, cyber-bullying is a common experience for many young people. Continual use of SNS signifies the importance of examining its links to cyber-bullying. This study examined the relationship between online social networking and the experience of cyber-bullying. A total of 400 participants (Mage=14.31 years) completed an online survey which examined the perceived definitions and frequency of cyber-bullying. Users of SNS reported significantly higher frequencies of stranger contact compared to non-users. Spearman's rho correlations determined no significant relationship between daily time on SNS and the frequency of stranger contact. This suggests that ownership of a SNS profile may be a stronger predictor of some cyber-bullying experiences compared to time spent on these sites. Findings encourage continued research on the nature of internet activities used by young adolescents and the possible exposure to online victimization.

  8. Enhanced online convolutional neural networks for object tracking

    Science.gov (United States)

    Zhang, Dengzhuo; Gao, Yun; Zhou, Hao; Li, Tianwen

    2018-04-01

    In recent several years, object tracking based on convolution neural network has gained more and more attention. The initialization and update of convolution filters can directly affect the precision of object tracking effective. In this paper, a novel object tracking via an enhanced online convolution neural network without offline training is proposed, which initializes the convolution filters by a k-means++ algorithm and updates the filters by an error back-propagation. The comparative experiments of 7 trackers on 15 challenging sequences showed that our tracker can perform better than other trackers in terms of AUC and precision.

  9. The Security of Organizations and Individuals in Online Social Networks

    OpenAIRE

    Elyashar, Aviad

    2016-01-01

    The serious privacy and security problems related to online social networks (OSNs) are what fueled two complementary studies as part of this thesis. In the first study, we developed a general algorithm for the mining of data of targeted organizations by using Facebook (currently the most popular OSN) and socialbots. By friending employees in a targeted organization, our active socialbots were able to find new employees and informal organizational links that we could not find by crawling with ...

  10. Leaking privacy and shadow profiles in online social networks

    OpenAIRE

    Garcia, David

    2017-01-01

    Social interaction and data integration in the digital society can affect the control that individuals have on their privacy. Social networking sites can access data from other services, including user contact lists where nonusers are listed too. Although most research on online privacy has focused on inference of personal information of users, this data integration poses the question of whether it is possible to predict personal information of nonusers. This article tests the shadow profile ...

  11. Analyzing the Social Networks of High- and Low-Performing Students in Online Discussion Forums

    Science.gov (United States)

    Ghadirian, Hajar; Salehi, Keyvan; Ayub, Ahmad Fauzi Mohd

    2018-01-01

    An ego network is an individual's social network relationships with core members. In this study, the ego network parameters in online discussion spaces of high- and low-performing students were compared. The extent to which students' ego networks changed over the course were also analyzed. Participation in 7 weeks of online discussions were…

  12. Composition and structure of a large online social network in The Netherlands.

    Directory of Open Access Journals (Sweden)

    Rense Corten

    Full Text Available Limitations in data collection have long been an obstacle in research on friendship networks. Most earlier studies use either a sample of ego-networks, or complete network data on a relatively small group (e.g., a single organization. The rise of online social networking services such as Friendster and Facebook, however, provides researchers with opportunities to study friendship networks on a much larger scale. This study uses complete network data from Hyves, a popular online social networking service in The Netherlands, comprising over eight million members and over 400 million online friendship relations. In the first study of its kind for The Netherlands, I examine the structure of this network in terms of the degree distribution, characteristic path length, clustering, and degree assortativity. Results indicate that this network shares features of other large complex networks, but also deviates in other respects. In addition, a comparison with other online social networks shows that these networks show remarkable similarities.

  13. Composition and structure of a large online social network in The Netherlands.

    Science.gov (United States)

    Corten, Rense

    2012-01-01

    Limitations in data collection have long been an obstacle in research on friendship networks. Most earlier studies use either a sample of ego-networks, or complete network data on a relatively small group (e.g., a single organization). The rise of online social networking services such as Friendster and Facebook, however, provides researchers with opportunities to study friendship networks on a much larger scale. This study uses complete network data from Hyves, a popular online social networking service in The Netherlands, comprising over eight million members and over 400 million online friendship relations. In the first study of its kind for The Netherlands, I examine the structure of this network in terms of the degree distribution, characteristic path length, clustering, and degree assortativity. Results indicate that this network shares features of other large complex networks, but also deviates in other respects. In addition, a comparison with other online social networks shows that these networks show remarkable similarities.

  14. How People Interact in Evolving Online Affiliation Networks

    Science.gov (United States)

    Gallos, Lazaros K.; Rybski, Diego; Liljeros, Fredrik; Havlin, Shlomo; Makse, Hernán A.

    2012-07-01

    The study of human interactions is of central importance for understanding the behavior of individuals, groups, and societies. Here, we observe the formation and evolution of networks by monitoring the addition of all new links, and we analyze quantitatively the tendencies used to create ties in these evolving online affiliation networks. We show that an accurate estimation of these probabilistic tendencies can be achieved only by following the time evolution of the network. Inferences about the reason for the existence of links using statistical analysis of network snapshots must therefore be made with great caution. Here, we start by characterizing every single link when the tie was established in the network. This information allows us to describe the probabilistic tendencies of tie formation and extract meaningful sociological conclusions. We also find significant differences in behavioral traits in the social tendencies among individuals according to their degree of activity, gender, age, popularity, and other attributes. For instance, in the particular data sets analyzed here, we find that women reciprocate connections 3 times as much as men and that this difference increases with age. Men tend to connect with the most popular people more often than women do, across all ages. On the other hand, triangular tie tendencies are similar, independent of gender, and show an increase with age. These results require further validation in other social settings. Our findings can be useful to build models of realistic social network structures and to discover the underlying laws that govern establishment of ties in evolving social networks.

  15. Vaccine Hesitancy and Online Information: The Influence of Digital Networks.

    Science.gov (United States)

    Getman, Rebekah; Helmi, Mohammad; Roberts, Hal; Yansane, Alfa; Cutler, David; Seymour, Brittany

    2017-12-01

    This article analyzes the digital childhood vaccination information network for vaccine-hesitant parents. The goal of this study was to explore the structure and influence of vaccine-hesitant content online by generating a database and network analysis of vaccine-relevant content. We used Media Cloud, a searchable big-data platform of over 550 million stories from 50,000 media sources, for quantitative and qualitative study of an online media sample based on keyword selection. We generated a hyperlink network map and measured indegree centrality of the sources and vaccine sentiment for a random sample of 450 stories. 28,122 publications from 4,817 sources met inclusion criteria. Clustered communities formed based on shared hyperlinks; communities tended to link within, not among, each other. The plurality of information was provaccine (46.44%, 95% confidence interval [39.86%, 53.20%]). The most influential sources were in the health community (National Institutes of Health, Centers for Disease Control and Prevention) or mainstream media ( New York Times); some user-generated sources also had strong influence and were provaccine (Wikipedia). The vaccine-hesitant community rarely interacted with provaccine content and simultaneously used primary provaccine content within vaccine-hesitant narratives. The sentiment of the overall conversation was consistent with scientific evidence. These findings demonstrate an online environment where scientific evidence online drives vaccine information outside of the vaccine-hesitant community but is also prominently used and misused within the robust vaccine-hesitant community. Future communication efforts should take current context into account; more information may not prevent vaccine hesitancy.

  16. Online social network sites and social capital: a case of facebook

    OpenAIRE

    Naseri, Samaneh

    2017-01-01

    The present study is a theoretical and literary review of online social network sites and their impact on social capital. In this review, the Facebook is selected as one popular and important online social networking site in the world today. To This end, first two main concepts of social capital, bridging and bonding social capital has been provided. Next, the concept of online social networks and the impact of FB on social networks are discussed.

  17. Effective seeding strategy in evolutionary prisoner's dilemma games on online social networks

    Science.gov (United States)

    Xu, Bo; Shi, Huibin; Wang, Jianwei; Huang, Yun

    2015-04-01

    This paper explores effective seeding strategies in prisoner's dilemma game (PDG) on online social networks, i.e. the optimal strategy to obtain global cooperation with minimum cost. Three distinct seeding strategies are compared by performing computer simulations on real online social network datasets. Our finding suggests that degree centrality seeding outperforms other strategies regardless of the initial payoff setting or network size. Celebrities of online social networks play key roles in preserving cooperation.

  18. Bridging online and offline social networks: Multiplex analysis

    Science.gov (United States)

    Filiposka, Sonja; Gajduk, Andrej; Dimitrova, Tamara; Kocarev, Ljupco

    2017-04-01

    We show that three basic actor characteristics, namely normalized reciprocity, three cycles, and triplets, can be expressed using an unified framework that is based on computing the similarity index between two sets associated with the actor: the set of her/his friends and the set of those considering her/him as a friend. These metrics are extended to multiplex networks and then computed for two friendship networks generated by collecting data from two groups of undergraduate students. We found that in offline communication strong and weak ties are (almost) equally presented, while in online communication weak ties are dominant. Moreover, weak ties are much less reciprocal than strong ties. However, across different layers of the multiplex network reciprocities are preserved, while triads (measured with normalized three cycles and triplets) are not significant.

  19. An information search model for online social Networks - MOBIRSE

    Directory of Open Access Journals (Sweden)

    Miguel Angel Niño Zambrano

    2015-09-01

    Full Text Available Online Social Networks (OSNs have been gaining great importance among Internet users in recent years.  These are sites where it is possible to meet people, publish, and share content in a way that is both easy and free of charge. As a result, the volume of information contained in these websites has grown exponentially, and web search has consequently become an important tool for users to easily find information relevant to their social networking objectives. Making use of ontologies and user profiles can make these searches more effective. This article presents a model for Information Retrieval in OSNs (MOBIRSE based on user profile and ontologies which aims to improve the relevance of retrieved information on these websites. The social network Facebook was chosen for a case study and as the instance for the proposed model. The model was validated using measures such as At-k Precision and Kappa statistics, to assess its efficiency.

  20. Designing for Learning: Online Social Networks as a Classroom Environment

    Directory of Open Access Journals (Sweden)

    Gail Casey

    2011-11-01

    Full Text Available This paper deploys notions of emergence, connections, and designs for learning to conceptualize high school students’ interactions when using online social media as a learning environment. It makes links to chaos and complexity theories and to fractal patterns as it reports on a part of the first author’s action research study, conducted while she was a teacher working in an Australian public high school and completing her PhD. The study investigates the use of a Ning online social network as a learning environment shared by seven classes, and it examines students’ reactions and online activity while using a range of social media and Web 2.0 tools.The authors use Graham Nuthall’s (2007 “lens on learning” to explore the social processes and culture of this shared online classroom. The paper uses his extensive body of research and analyses of classroom learning processes to conceptualize and analyze data throughout the action research cycle. It discusses the pedagogical implications that arise from the use of social media and, in so doing, challenges traditional models of teaching and learning.

  1. Semantic network analysis of vaccine sentiment in online social media.

    Science.gov (United States)

    Kang, Gloria J; Ewing-Nelson, Sinclair R; Mackey, Lauren; Schlitt, James T; Marathe, Achla; Abbas, Kaja M; Swarup, Samarth

    2017-06-22

    To examine current vaccine sentiment on social media by constructing and analyzing semantic networks of vaccine information from highly shared websites of Twitter users in the United States; and to assist public health communication of vaccines. Vaccine hesitancy continues to contribute to suboptimal vaccination coverage in the United States, posing significant risk of disease outbreaks, yet remains poorly understood. We constructed semantic networks of vaccine information from internet articles shared by Twitter users in the United States. We analyzed resulting network topology, compared semantic differences, and identified the most salient concepts within networks expressing positive, negative, and neutral vaccine sentiment. The semantic network of positive vaccine sentiment demonstrated greater cohesiveness in discourse compared to the larger, less-connected network of negative vaccine sentiment. The positive sentiment network centered around parents and focused on communicating health risks and benefits, highlighting medical concepts such as measles, autism, HPV vaccine, vaccine-autism link, meningococcal disease, and MMR vaccine. In contrast, the negative network centered around children and focused on organizational bodies such as CDC, vaccine industry, doctors, mainstream media, pharmaceutical companies, and United States. The prevalence of negative vaccine sentiment was demonstrated through diverse messaging, framed around skepticism and distrust of government organizations that communicate scientific evidence supporting positive vaccine benefits. Semantic network analysis of vaccine sentiment in online social media can enhance understanding of the scope and variability of current attitudes and beliefs toward vaccines. Our study synthesizes quantitative and qualitative evidence from an interdisciplinary approach to better understand complex drivers of vaccine hesitancy for public health communication, to improve vaccine confidence and vaccination coverage

  2. Towards a deep understanding of malware propagation in online social networks

    Energy Technology Data Exchange (ETDEWEB)

    Yan, Guanhua [Los Alamos National Laboratory; Eidenbenz, Stephan [Los Alamos National Laboratory; Chen, Guanling [U OF MASSACHUSETTS LOWELL; Li, Nan [U OF MASSACHUSETTS LOWELL

    2009-01-01

    Online social networks, which have been expanding at a blistering speed in the recent years, have emerged as a popular communication infrastructure for Internet users. Meanwhile, malware that specifically targets these online social networks are also on the rise. In this work, we aim to investigate the characteristics of malware propagation in online social networks. Our study is based on a dataset collected from a real-world location-based online social network. We analyze the social structure and user activity patterns of this network. We further use extensive trace-driven simulation to study the impact of initial infection, user click probability, social structure, and activity patterns on malware propagation in online social networks. The results from this work has greatly deepened our understanding of the nature of online social network malware and also shed light on how to defend against them effectively.

  3. Characteristics of Social Network Gamers: Results of an Online Survey.

    Science.gov (United States)

    Geisel, Olga; Panneck, Patricia; Stickel, Anna; Schneider, Michael; Müller, Christian A

    2015-01-01

    Current research on Internet addiction (IA) reported moderate to high prevalence rates of IA and comorbid psychiatric symptoms in users of social networking sites (SNS) and online role-playing games. The aim of this study was to characterize adult users of an Internet multiplayer strategy game within a SNS. Therefore, we conducted an exploratory study using an online survey to assess sociodemographic variables, psychopathology, and the rate of IA in a sample of adult social network gamers by Young's Internet Addiction Test (IAT), the Toronto Alexithymia Scale (TAS-26), the Beck Depression Inventory-II (BDI-II), the Symptom Checklist-90-R (SCL-90-R), and the WHO Quality of Life-BREF (WHOQOL-BREF). All participants were listed gamers of "Combat Zone" in the SNS "Facebook." In this sample, 16.2% of the participants were categorized as subjects with IA and 19.5% fulfilled the criteria for alexithymia. Comparing study participants with and without IA, the IA group had significantly more subjects with alexithymia, reported more depressive symptoms, and showed poorer quality of life. These findings suggest that social network gaming might also be associated with maladaptive patterns of Internet use. Furthermore, a relationship between IA, alexithymia, and depressive symptoms was found that needs to be elucidated by future studies.

  4. Choosing your network: social preferences in an online health community.

    Science.gov (United States)

    Centola, Damon; van de Rijt, Arnout

    2015-01-01

    A growing number of online health communities offer individuals the opportunity to receive information, advice, and support from peers. Recent studies have demonstrated that these new online contacts can be important informational resources, and can even exert significant influence on individuals' behavior in various contexts. However little is known about how people select their health contacts in these virtual domains. This is because selection preferences in peer networks are notoriously difficult to detect. In existing networks, unobserved pressures on tie formation--such as common organizational memberships, introductions to friends of friends, or limitations on accessibility--may mistakenly be interpreted as individual preferences for interacting/not interacting with others. We address these issues by adopting a social media approach to studying network formation. We study social selection using an in vivo study within an online exercise program, in which anonymous participants have equal opportunities for initiating relationships with other program members. This design allows us to identify individuals' preferences for health contacts, and to evaluate what these preferences imply for members' access to new kinds of health information, and for the kinds of social influences to which they are exposed. The study was conducted within a goal-oriented fitness competition, in which participation was greatest among a small core of active individuals. Our results show that the active participants displayed indifference to the fitness and exercise profiles of others, disregarding information about others' fitness levels, exercise preferences, and workout experiences, instead selecting partners almost entirely on the basis of similarities on gender, age, and BMI. Interestingly, the findings suggest that rather than expanding and diversifying their sources of health information, participants' choices limited the value of their online resources by selecting contacts

  5. Entrepreneur online social networks: structure, diversity and impact on start-up survival

    NARCIS (Netherlands)

    Song, Y.; Vinig, T.

    2012-01-01

    In this paper, we discuss the results of a pilot study in which we use a novel approach to collect entrepreneur online social network data from LinkedIn, Facebook and Twitter. We studied the size and structure of entrepreneur social networks by analysing the online network industry and location

  6. Analyzing the Dynamics of Communication in Online Social Networks

    Science.gov (United States)

    de Choudhury, Munmun; Sundaram, Hari; John, Ajita; Seligmann, Doree Duncan

    This chapter deals with the analysis of interpersonal communication dynamics in online social networks and social media. Communication is central to the evolution of social systems. Today, the different online social sites feature variegated interactional affordances, ranging from blogging, micro-blogging, sharing media elements (i.e., image, video) as well as a rich set of social actions such as tagging, voting, commenting and so on. Consequently, these communication tools have begun to redefine the ways in which we exchange information or concepts, and how the media channels impact our online interactional behavior. Our central hypothesis is that such communication dynamics between individuals manifest themselves via two key aspects: the information or concept that is the content of communication, and the channel i.e., the media via which communication takes place. We present computational models and discuss large-scale quantitative observational studies for both these organizing ideas. First, we develop a computational framework to determine the "interestingness" property of conversations cented around rich media. Second, we present user models of diffusion of social actions and study the impact of homophily on the diffusion process. The outcome of this research is twofold. First, extensive empirical studies on datasets from YouTube have indicated that on rich media sites, the conversations that are deemed "interesting" appear to have consequential impact on the properties of the social network they are associated with: in terms of degree of participation of the individuals in future conversations, thematic diffusion as well as emergent cohesiveness in activity among the concerned participants in the network. Second, observational and computational studies on large social media datasets such as Twitter have indicated that diffusion of social actions in a network can be indicative of future information cascades. Besides, given a topic, these cascades are often a

  7. Employment relations: A data driven analysis of job markets using online job boards and online professional networks

    CSIR Research Space (South Africa)

    Marivate, Vukosi N

    2017-08-01

    Full Text Available Data from online job boards and online professional networks present an opportunity to understand job markets as well as how professionals transition from one job/career to another. We propose a data driven approach to begin to understand a slice...

  8. The strategic impact of social networks on the online gaming industry : strategic use of technology

    OpenAIRE

    Sousa, Sofia Taveira de

    2012-01-01

    This dissertation focuses on assessing the strategic potential of social networks by answering the following research question: Is there any strategic impact of social networks on the online gaming industry? In order to analyze the strategic potential of social networks for online games, we identify the main factors that online players consider as crucial for them to keep playing. These factors can either be related to the game’s strategy itself, such as all the details, graphics and ambig...

  9. Continuous Online Sequence Learning with an Unsupervised Neural Network Model.

    Science.gov (United States)

    Cui, Yuwei; Ahmad, Subutar; Hawkins, Jeff

    2016-09-14

    The ability to recognize and predict temporal sequences of sensory inputs is vital for survival in natural environments. Based on many known properties of cortical neurons, hierarchical temporal memory (HTM) sequence memory recently has been proposed as a theoretical framework for sequence learning in the cortex. In this letter, we analyze properties of HTM sequence memory and apply it to sequence learning and prediction problems with streaming data. We show the model is able to continuously learn a large number of variableorder temporal sequences using an unsupervised Hebbian-like learning rule. The sparse temporal codes formed by the model can robustly handle branching temporal sequences by maintaining multiple predictions until there is sufficient disambiguating evidence. We compare the HTM sequence memory with other sequence learning algorithms, including statistical methods: autoregressive integrated moving average; feedforward neural networks-time delay neural network and online sequential extreme learning machine; and recurrent neural networks-long short-term memory and echo-state networks on sequence prediction problems with both artificial and real-world data. The HTM model achieves comparable accuracy to other state-of-the-art algorithms. The model also exhibits properties that are critical for sequence learning, including continuous online learning, the ability to handle multiple predictions and branching sequences with high-order statistics, robustness to sensor noise and fault tolerance, and good performance without task-specific hyperparameter tuning. Therefore, the HTM sequence memory not only advances our understanding of how the brain may solve the sequence learning problem but is also applicable to real-world sequence learning problems from continuous data streams.

  10. Effect of online social networking on employee productivity

    Directory of Open Access Journals (Sweden)

    A. Ferreira

    2009-02-01

    Full Text Available The popularity of social networking sites is relatively recent and the effect of online social networking (OSN on employee productivity has not received much scholarly attention. The reason most likely lies in the social nature of social networking sites and OSN, which is assumed to have a negative effect on employee productivity and not bear organisational benefit. This reseach investigated recent Internet developments as seen in the social Web and specifically investigated the effect of OSN on employee productivity and what some of the consequences would be if employees were allowed unrestricted access to these networks. The findings concerning the nature of employees' OSN activities, employees' attitude or perceptions with regard to OSN in the workplace and how OSN can contribute or affect the productivity of employees are discussed in this article. Some of the basic misconceptions regarding OSN are highlighted and it is concluded that this technology can be used to increase collaboration between individuals who share a common interest or goal. Increased collaboration will stimulate knowledge sharing between individuals, with the possible effect of increased productivity. However, the risks associated with OSN should be noted, such as loss of privacy, bandwidth and storage consumption, exposure to malware and lower employee productivity.

  11. LHCb: Time structure analysis of the LHCb Online network

    CERN Multimedia

    Antichi, G; Campora Perez, D H; Liu, G; Neufeld, N; Giordano, S; Owezarski, P; Moore, A

    2013-01-01

    The LHCb Online Network is a real time high performance network, in which 350 data sources send data over a Gigabit Ethernet LAN to more than 1500 receiving nodes. The aggregated throughput of the application, called Event Building, is more than 60 GB/s. The protocol employed by LHCb makes the sending nodes transmit simultaneously portions of events to one receiving node at a time, which is selected using a credit-token scheme. The resulting traffic is very bursty and sensitive to irregularities in the temporal distribution of packet-bursts to the same destination or region of the network. In order to study the relevant properties of such a dataflow, a non-disruptive monitoring setup based on a networking capable FPGA (NetFPGA) has been deployed. The NetFPGA allows order of hundred nano-second precise time-stamping of packets. We study in detail the timing structure of the Event Building communication, and we identify potential effects of micro-bursts like buffer packet drops or jitter.

  12. Network characteristics for server selection in online games

    Science.gov (United States)

    Claypool, Mark

    2008-01-01

    Online gameplay is impacted by the network characteristics of players connected to the same server. Unfortunately, the network characteristics of online game servers are not well-understood, particularly for groups that wish to play together on the same server. As a step towards a remedy, this paper presents analysis of an extensive set of measurements of game servers on the Internet. Over the course of many months, actual Internet game servers were queried simultaneously by twenty-five emulated game clients, with both servers and clients spread out on the Internet. The data provides statistics on the uptime and populations of game servers over a month long period an an in-depth look at the suitability for game servers for multi-player server selection, concentrating on characteristics critical to playability--latency and fairness. Analysis finds most game servers have latencies suitable for third-person and omnipresent games, such as real-time strategy, sports and role-playing games, providing numerous server choices for game players. However, far fewer game servers have the low latencies required for first-person games, such as shooters or race games. In all cases, groups that wish to play together have a greatly reduced set of servers from which to choose because of inherent unfairness in server latencies and server selection is particularly limited as the group size increases. These results hold across different game types and even across different generations of games. The data should be useful for game developers and network researchers that seek to improve game server selection, whether for single or multiple players.

  13. Tracking social contact networks with online respondent-driven detection : who recruits whom?

    NARCIS (Netherlands)

    Stein, Mart L.; van der Heijden, P.G.M.; Buskens, V.W.; van Steenbergen, Jim E.; Bengtsson, Linus; Koppeschaar, Carl E.; Thorson, Anna E.; Kretzschmar, Mirjam E. E.

    2015-01-01

    Background: Transmission of respiratory pathogens in a population depends on the contact network patterns of individuals. To accurately understand and explain epidemic behaviour information on contact networks is required, but only limited empirical data is available. Online respondent-driven

  14. Tracking social contact networks with online respondent-driven detection : who recruits whom?

    NARCIS (Netherlands)

    Stein, Mart L; van der Heijden, Peter G M; Buskens, Vincent; van Steenbergen, Jim E; Bengtsson, Linus; Koppeschaar, Carl E; Thorson, Anna; Kretzschmar, MEE

    2015-01-01

    BACKGROUND: Transmission of respiratory pathogens in a population depends on the contact network patterns of individuals. To accurately understand and explain epidemic behaviour information on contact networks is required, but only limited empirical data is available. Online respondent-driven

  15. SEIR Model of Rumor Spreading in Online Social Network with Varying Total Population Size

    International Nuclear Information System (INIS)

    Dong Suyalatu; Deng Yan-Bin; Huang Yong-Chang

    2017-01-01

    Based on the infectious disease model with disease latency, this paper proposes a new model for the rumor spreading process in online social network. In this paper what we establish an SEIR rumor spreading model to describe the online social network with varying total number of users and user deactivation rate. We calculate the exact equilibrium points and reproduction number for this model. Furthermore, we perform the rumor spreading process in the online social network with increasing population size based on the original real world Facebook network. The simulation results indicate that the SEIR model of rumor spreading in online social network with changing total number of users can accurately reveal the inherent characteristics of rumor spreading process in online social network . (paper)

  16. SEIR Model of Rumor Spreading in Online Social Network with Varying Total Population Size

    Science.gov (United States)

    Dong, Suyalatu; Deng, Yan-Bin; Huang, Yong-Chang

    2017-10-01

    Based on the infectious disease model with disease latency, this paper proposes a new model for the rumor spreading process in online social network. In this paper what we establish an SEIR rumor spreading model to describe the online social network with varying total number of users and user deactivation rate. We calculate the exact equilibrium points and reproduction number for this model. Furthermore, we perform the rumor spreading process in the online social network with increasing population size based on the original real world Facebook network. The simulation results indicate that the SEIR model of rumor spreading in online social network with changing total number of users can accurately reveal the inherent characteristics of rumor spreading process in online social network. Supported by National Natural Science Foundation of China under Grant Nos. 11275017 and 11173028

  17. Does Sentiment Among Users in Online Social Networks Polarize or Balance Out?

    DEFF Research Database (Denmark)

    Trier, Matthias; Hillmann, Robert

    2017-01-01

    Users express and share sentiments electronically when they communicate within online social network applications. One way to analyze such interdependent data is focusing on the inter-user relationships by applying a sociological perspective based on social network analysis. Existing studies exam...... examined the existence or distribution of sentiments in online communication at a general level or in small observed groups....

  18. Professional Online Presence and Learning Networks: Educating for Ethical Use of Social Media

    Science.gov (United States)

    Forbes, Dianne

    2017-01-01

    In a teacher education context, this study considers the use of social media for building a professional online presence and learning network. This article provides an overview of uses of social media in teacher education, presents a case study of key processes in relation to professional online presence and learning networks, and highlights…

  19. Information Filtering via Heterogeneous Diffusion in Online Bipartite Networks.

    Science.gov (United States)

    Zhang, Fu-Guo; Zeng, An

    2015-01-01

    The rapid expansion of Internet brings us overwhelming online information, which is impossible for an individual to go through all of it. Therefore, recommender systems were created to help people dig through this abundance of information. In networks composed by users and objects, recommender algorithms based on diffusion have been proven to be one of the best performing methods. Previous works considered the diffusion process from user to object, and from object to user to be equivalent. We show in this work that it is not the case and we improve the quality of the recommendation by taking into account the asymmetrical nature of this process. We apply this idea to modify the state-of-the-art recommendation methods. The simulation results show that the new methods can outperform these existing methods in both recommendation accuracy and diversity. Finally, this modification is checked to be able to improve the recommendation in a realistic case.

  20. Gender Differences in the Continuance of Online Social Networks

    Science.gov (United States)

    Shi, Na; Cheung, Christy M. K.; Lee, Matthew K. O.; Chen, Huaping

    Social network sites (SNS) have become increasingly popular in the past few years benefiting from the rapid growth of Web 2.0 applications. However, research on the adoption and usage of SNS is limited. In this study, we attempt to understand users' continuance intention to use SNS and investigate the role of gender. A research model was developed and tested with 213 respondents from an online survey. The results confirm that users' continuance intention to use SNS is strongly determined by satisfaction. The effect of disconfirmation of maintaining offline contacts on satisfaction is more important for women, while the effect of disconfirmation of entertainment is more salient for men. Implications of this study for both researchers and practitioners are discussed.

  1. Fuzzy Modelling for Human Dynamics Based on Online Social Networks.

    Science.gov (United States)

    Cuenca-Jara, Jesus; Terroso-Saenz, Fernando; Valdes-Vela, Mercedes; Skarmeta, Antonio F

    2017-08-24

    Human mobility mining has attracted a lot of attention in the research community due to its multiple implications in the provisioning of innovative services for large metropolises. In this scope, Online Social Networks (OSN) have arisen as a promising source of location data to come up with new mobility models. However, the human nature of this data makes it rather noisy and inaccurate. In order to deal with such limitations, the present work introduces a framework for human mobility mining based on fuzzy logic. Firstly, a fuzzy clustering algorithm extracts the most active OSN areas at different time periods. Next, such clusters are the building blocks to compose mobility patterns. Furthermore, a location prediction service based on a fuzzy rule classifier has been developed on top of the framework. Finally, both the framework and the predictor has been tested with a Twitter and Flickr dataset in two large cities.

  2. Efficient Online Learning Algorithms Based on LSTM Neural Networks.

    Science.gov (United States)

    Ergen, Tolga; Kozat, Suleyman Serdar

    2017-09-13

    We investigate online nonlinear regression and introduce novel regression structures based on the long short term memory (LSTM) networks. For the introduced structures, we also provide highly efficient and effective online training methods. To train these novel LSTM-based structures, we put the underlying architecture in a state space form and introduce highly efficient and effective particle filtering (PF)-based updates. We also provide stochastic gradient descent and extended Kalman filter-based updates. Our PF-based training method guarantees convergence to the optimal parameter estimation in the mean square error sense provided that we have a sufficient number of particles and satisfy certain technical conditions. More importantly, we achieve this performance with a computational complexity in the order of the first-order gradient-based methods by controlling the number of particles. Since our approach is generic, we also introduce a gated recurrent unit (GRU)-based approach by directly replacing the LSTM architecture with the GRU architecture, where we demonstrate the superiority of our LSTM-based approach in the sequential prediction task via different real life data sets. In addition, the experimental results illustrate significant performance improvements achieved by the introduced algorithms with respect to the conventional methods over several different benchmark real life data sets.

  3. "Newbies" and "Celebrities": Detecting Social Roles in an Online Network of Teachers via Participation Patterns

    Science.gov (United States)

    Smith Risser, H.; Bottoms, SueAnn

    2014-01-01

    The advent of social networking tools allows teachers to create online networks and share information. While some virtual networks have a formal structure and defined boundaries, many do not. These unstructured virtual networks are difficult to study because they lack defined boundaries and a formal structure governing leadership roles and the…

  4. Facebook and romantic relationships: intimacy and couple satisfaction associated with online social network use.

    Science.gov (United States)

    Hand, Matthew M; Thomas, Donna; Buboltz, Walter C; Deemer, Eric D; Buyanjargal, Munkhsanaa

    2013-01-01

    Online social networks, such as Facebook, have gained immense popularity and potentially affect the way people build and maintain interpersonal relationships. The present study sought to examine time spent on online social networks, as it relates to intimacy and relationship satisfaction experienced in romantic relationships. Results did not find relationships between an individual's usage of online social networks and his/her perception of relationship satisfaction and intimacy. However, the study found a negative relationship between intimacy and the perception of a romantic partner's use of online social networks. This finding may allude to an attributional bias in which individuals are more likely to perceive a partner's usage as negative compared to their own usage. Additionally, it was found that intimacy mediates the relationship between online social network usage and overall relationship satisfaction, which suggests that the level of intimacy experienced in a relationship may serve as a buffer that protects the overall level of satisfaction.

  5. Quantifying Users' Interconnectedness in Online Social Networks - An Indispensible Step for Economic Valuation

    Science.gov (United States)

    Gneiser, Martin; Heidemann, Julia; Klier, Mathias; Landherr, Andrea; Probst, Florian

    Online social networks have been gaining increasing economic importance in light of the rising number of their users. Numerous recent acquisitions priced at enormous amounts have illustrated this development and revealed the need for adequate business valuation models. The value of an online social network is largely determined by the value of its users, the relationships between these users, and the resulting network effects. Therefore, the interconnectedness of a user within the network has to be considered explicitly to get a reasonable estimate for the economic value. Established standard business valuation models, however, do not sufficiently take these aspects into account. Thus, we propose a measure based on the PageRank-algorithm to quantify users’ interconnectedness in an online social network. This is a first but indispensible step towards an adequate economic valuation of online social networks.

  6. Modern Social Support Structures: Online Social Networks and their Implications for Social Workers

    Directory of Open Access Journals (Sweden)

    Kala Chakradhar

    2009-03-01

    Full Text Available Mapping and assessing social networks and the quality of their social support is a valuable intervention strategy for social workers. These networks have now spread onto the digital realm in the form of Online Social Networks (OSNs. This study investigated the nature of social support provided by such networks to their users in a rural mid-South University (USA and explored parallels with the current understanding of social support in conventional social networks. A web-based survey administered to college students revealed that users of these online networks were predominantly undergraduate first year students, female, single, unemployed and from a variety of academic disciplines. The examination of the components of OSNs appears to mirror those of offline networks. They also seem to complement the effects of each other while contributing to an individual's support system. The paper concludes with critical implications of such online social networking for University students and social workers in practice and education.

  7. Addiction to Internet Use, Online Gaming, and Online Social Networking Among Young Adults in China, Singapore, and the United States.

    Science.gov (United States)

    Tang, Catherine So-Kum; Koh, Yee Woen; Gan, YiQun

    2017-11-01

    The current study investigated the rates of addictions to Internet use, online gaming, and online social networking as well as their associations with depressive symptoms among young adults in China, Singapore, and the United States. A total of 3267 undergraduate students were recruited. Psychological instruments were used to assess various Internet-related addictions and depressive symptoms. Male students were more addicted to Internet and online gaming whereas female students were more addicted to online social networking. Compared with students in the United States, Chinese and Singaporean students were more addicted to Internet use and online social networking but less to online gaming. The odds of depression among students with addiction to various Internet-related addictions were highest in China. Internet-related addiction is a new public health concern of young adults, especially in the Asia-Pacific regions. It is found to associate with depressive symptoms. Strategies should address this phenomenon with attention to specific needs of gender and region while managing mood disturbances.

  8. A Comparison of Online Social Networks and Real-Life Social Networks: A Study of Sina Microblogging

    Directory of Open Access Journals (Sweden)

    Dayong Zhang

    2014-01-01

    Full Text Available Online social networks appear to enrich our social life, which raises the question whether they remove cognitive constraints on human communication and improve human social capabilities. In this paper, we analyze the users' following and followed relationships based on the data of Sina Microblogging and reveal several structural properties of Sina Microblogging. Compared with real-life social networks, our results confirm some similar features. However, Sina Microblogging also shows its own specialties, such as hierarchical structure and degree disassortativity, which all mark a deviation from real-life social networks. The low cost of the online network forms a broader perspective, and the one-way link relationships make it easy to spread information, but the online social network does not make too much difference in the creation of strong interpersonal relationships. Finally, we describe the mechanisms for the formation of these characteristics and discuss the implications of these structural properties for the real-life social networks.

  9. Similarity between community structures of different online social networks and its impact on underlying community detection

    Science.gov (United States)

    Fan, W.; Yeung, K. H.

    2015-03-01

    As social networking services are popular, many people may register in more than one online social network. In this paper we study a set of users who have accounts of three online social networks: namely Foursquare, Facebook and Twitter. Community structure of this set of users may be reflected in these three online social networks. Therefore, high correlation between these reflections and the underlying community structure may be observed. In this work, community structures are detected in all three online social networks. Also, we investigate the similarity level of community structures across different networks. It is found that they show strong correlation with each other. The similarity between different networks may be helpful to find a community structure close to the underlying one. To verify this, we propose a method to increase the weights of some connections in networks. With this method, new networks are generated to assist community detection. By doing this, value of modularity can be improved and the new community structure match network's natural structure better. In this paper we also show that the detected community structures of online social networks are correlated with users' locations which are identified on Foursquare. This information may also be useful for underlying community detection.

  10. Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation.

    Science.gov (United States)

    Kwak, Doyeon; Kim, Wonjoon

    2017-01-01

    It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks.

  11. Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation.

    Directory of Open Access Journals (Sweden)

    Doyeon Kwak

    Full Text Available It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks.

  12. Monitoring of Students' Interaction in Online Learning Settings by Structural Network Analysis and Indicators.

    Science.gov (United States)

    Ammenwerth, Elske; Hackl, Werner O

    2017-01-01

    Learning as a constructive process works best in interaction with other learners. Support of social interaction processes is a particular challenge within online learning settings due to the spatial and temporal distribution of participants. It should thus be carefully monitored. We present structural network analysis and related indicators to analyse and visualize interaction patterns of participants in online learning settings. We validate this approach in two online courses and show how the visualization helps to monitor interaction and to identify activity profiles of learners. Structural network analysis is a feasible approach for an analysis of the intensity and direction of interaction in online learning settings.

  13. Characteristics of Social Network Gamers: in between Social Networking and Online Role-Playing Games

    Directory of Open Access Journals (Sweden)

    Olga eGeisel

    2015-07-01

    Full Text Available Current research on internet addiction (IA reported moderate to high prevalence rates of IA and comorbid psychiatric symptoms in users of social networking sites (SNS and online role-playing games. The aim of this study was to characterise adult users of an internet multiplayer strategy game within a SNS. Therefore, we conducted an exploratory study using an online survey to assess sociodemographic variables, psychopathology and the rate of IA in a sample of adult social network gamers by Young´s Internet Addiction Test (IAT, the Toronto Alexithymia Scale (TAS, the Beck Depression Inventory II (BDI-II, the Symptom Checklist-90-R (SCL-90-R and the WHO Quality of Life-BREF (WHOQOL-BREF. All participants were listed gamers of combat zone in the SNS Facebook. In the IAT analysis, 16.2 % of the participants (n = 60 were categorized as subjects with IA and 19.5 % (n = 72 fulfilled the criteria for alexithymia. Comparing study participants with and without IA, the IA group had significantly more subjects with alexithymia, reported more depressive symptoms, and showed poorer quality of life. These findings suggest that social network gaming might also be associated with maladaptive patterns of internet use. Furthermore, a relationship between IA, alexithymia and depressive symptoms was found that needs to be elucidated by future studies.

  14. Communication, collaboration and identity: factor analysis of academics’ perceptions of online networking

    Directory of Open Access Journals (Sweden)

    Katy Jordan

    2018-04-01

    Full Text Available Since the advent of online social networking sites, much has been written about their potential for transforming academia, as communication and collaboration underpin many scholarly activities. However, the extent to which these benefits are being realised in practice is unclear. As the uptake of tools by academics continues to grow, there is a question as to whether differences exist in their use and if any patterns or underlying factors are at play. This article presents the results of an online survey addressing this gap. A disciplinary divide was evident in terms of preferred academic social networking platforms, while perceptions about how academics use online networking for different purposes are linked to job position. Exploratory factor analysis identified four components representing different strategies used by academics in their approaches to online networking, including maintaining a personal learning network, promoting the professional self, seeking and promoting publications, and advancing careers.

  15. Offline Social Relationships and Online Cancer Communication: Effects of Social and Family Support on Online Social Network Building.

    Science.gov (United States)

    Namkoong, Kang; Shah, Dhavan V; Gustafson, David H

    2017-11-01

    This study investigates how social support and family relationship perceptions influence breast cancer patients' online communication networks in a computer-mediated social support (CMSS) group. To examine social interactions in the CMSS group, we identified two types of online social networks: open and targeted communication networks. The open communication network reflects group communication behaviors (i.e., one-to-many or "broadcast" communication) in which the intended audience is not specified; in contrast, the targeted communication network reflects interpersonal discourses (i.e., one-to-one or directed communication) in which the audience for the message is specified. The communication networks were constructed by tracking CMSS group usage data of 237 breast cancer patients who participated in one of two National Cancer Institute-funded randomized clinical trials. Eligible subjects were within 2 months of a diagnosis of primary breast cancer or recurrence at the time of recruitment. Findings reveal that breast cancer patients who perceived less availability of offline social support had a larger social network size in the open communication network. In contrast, those who perceived less family cohesion had a larger targeted communication network in the CMSS group, meaning they were inclined to use the CMSS group for developing interpersonal relationships.

  16. Online Help to End-Users in a Networked Environment.

    Science.gov (United States)

    Meyer, Paul

    1991-01-01

    Discusses the need for online help for end-users based on experiences with an online public access catalog (OPAC) at the University of Cape Town libraries. The concept of end users is examined, the role of search intermediaries in information systems is explained, and online help and systems design is discussed. (LRW)

  17. Multilabel user classification using the community structure of online networks.

    Science.gov (United States)

    Rizos, Georgios; Papadopoulos, Symeon; Kompatsiaris, Yiannis

    2017-01-01

    We study the problem of semi-supervised, multi-label user classification of networked data in the online social platform setting. We propose a framework that combines unsupervised community extraction and supervised, community-based feature weighting before training a classifier. We introduce Approximate Regularized Commute-Time Embedding (ARCTE), an algorithm that projects the users of a social graph onto a latent space, but instead of packing the global structure into a matrix of predefined rank, as many spectral and neural representation learning methods do, it extracts local communities for all users in the graph in order to learn a sparse embedding. To this end, we employ an improvement of personalized PageRank algorithms for searching locally in each user's graph structure. Then, we perform supervised community feature weighting in order to boost the importance of highly predictive communities. We assess our method performance on the problem of user classification by performing an extensive comparative study among various recent methods based on graph embeddings. The comparison shows that ARCTE significantly outperforms the competition in almost all cases, achieving up to 35% relative improvement compared to the second best competing method in terms of F1-score.

  18. Multilabel user classification using the community structure of online networks.

    Directory of Open Access Journals (Sweden)

    Georgios Rizos

    Full Text Available We study the problem of semi-supervised, multi-label user classification of networked data in the online social platform setting. We propose a framework that combines unsupervised community extraction and supervised, community-based feature weighting before training a classifier. We introduce Approximate Regularized Commute-Time Embedding (ARCTE, an algorithm that projects the users of a social graph onto a latent space, but instead of packing the global structure into a matrix of predefined rank, as many spectral and neural representation learning methods do, it extracts local communities for all users in the graph in order to learn a sparse embedding. To this end, we employ an improvement of personalized PageRank algorithms for searching locally in each user's graph structure. Then, we perform supervised community feature weighting in order to boost the importance of highly predictive communities. We assess our method performance on the problem of user classification by performing an extensive comparative study among various recent methods based on graph embeddings. The comparison shows that ARCTE significantly outperforms the competition in almost all cases, achieving up to 35% relative improvement compared to the second best competing method in terms of F1-score.

  19. A Novel, Privacy Preserving, Architecture for Online Social Networks

    Directory of Open Access Journals (Sweden)

    Zhe Wang

    2015-12-01

    Full Text Available The centralized nature of conventional OSNs poses serious risks to the privacy and security of information exchanged between their members. These risks prompted several attempts to create decentralized OSNs, or DOSNs. The basic idea underlying these attempts, is that each member of a social network keeps its data under its own control, instead of surrendering it to a central host, providing access to it to other members according to its own access-control policy. Unfortunately all existing versions of DOSNs have a very serious limitation. Namely, they are unable to subject the membership of a DOSN, and the interaction between its members, to any global policy—which is essential for many social communities. Moreover, the DOSN architecture is unable to support useful capabilities such as narrowcasting and profile based search. This paper describes a novel architecture of decentralized OSNs—called DOSC, for “online social community”. DOSC adopts the decentralization idea underlying DOSNs, but it is able to subject the membership of a DOSC-community, and the interaction between its members, to a wide range of policies, including privacy-preserving narrowcasting and profile-sensitive search.

  20. Popularity Evaluation Model for Microbloggers Online Social Network

    Directory of Open Access Journals (Sweden)

    Xia Zhang

    2014-01-01

    Full Text Available Recently, microblogging is widely studied by the researchers in the domain of the online social network (OSN. How to evaluate the popularities of microblogging users is an important research field, which can be applied to commercial advertising, user behavior analysis and information dissemination, and so forth. Previous studies on the evaluation methods cannot effectively solve and accurately evaluate the popularities of the microbloggers. In this paper, we proposed an electromagnetic field theory based model to analyze the popularities of microbloggers. The concept of the source in microblogging field is first put forward, which is based on the concept of source in the electromagnetic field; then, one’s microblogging flux is calculated according to his/her behaviors (send or receive feedbacks on the microblogging platform; finally, we used three methods to calculate one’s microblogging flux density, which can represent one’s popularity on the microblogging platform. In the experimental work, we evaluated our model using real microblogging data and selected the best one from the three popularity measure methods. We also compared our model with the classic PageRank algorithm; and the results show that our model is more effective and accurate to evaluate the popularities of the microbloggers.

  1. Online social networks for patient involvement and recruitment in clinical research.

    Science.gov (United States)

    Ryan, Gemma Sinead

    2013-01-01

    To review current literature and discuss the potential of online social networking to engage patients and the public and recruit and retain participants in clinical research. Online social networking is becoming a large influence on people's daily lives. Clinical research faces several challenges, with an increasing need to engage with patients and the public and for studies to recruit and retain increasing numbers of participants, particularly in under-served, under-represented and hard to reach groups and communities. Searches were conducted using EMBASE, BNI, ERIC, CINAHL, PSYCHinfo online databases and Google Scholar to identify any grey or unpublished literature that may be available. Review methods This is a methodology paper. Online social networking is a successful, cost-effective and efficient method by which to target and recruit a wide range of communities, adolescents, young people and underserved populations into quantitative and qualitative research. Retention of participants in longitudinal studies could be improved using social networks such as Facebook. Evidence indicates that a mixed approach to recruitment using social networking and traditional methods is most effective. Further research is required to strengthen the evidence available, especially in dissemination of research through online social networks. Researchers should consider using online social networking as a method of engaging the public, and also for the recruitment and follow up of participants.

  2. The Relationship Between Online Social Networking and Depression: A Systematic Review of Quantitative Studies.

    Science.gov (United States)

    Baker, David A; Algorta, Guillermo Perez

    2016-11-01

    Online social networking sites (SNSs) such as Facebook, Twitter, and MySpace are used by billions of people every day to communicate and interact with others. There has been increasing interest in the potential impact of online social networking on wellbeing, with a broadening body of new research into factors associated with both positive and negative mental health outcomes such as depression. This systematic review of empirical studies (n = 30) adds to existing research in this field by examining current quantitative studies focused on the relationship between online social networking and symptoms of depression. The academic databases PsycINFO, Web of Science, CINAHL, MEDLINE, and EMBASE were searched systematically using terms related to online social networking and depression. Reporting quality was critically appraised and the findings discussed with reference to their wider implications. The findings suggest that the relationship between online social networking and symptoms of depression may be complex and associated with multiple psychological, social, behavioral, and individual factors. Furthermore, the impact of online social networking on wellbeing may be both positive and negative, highlighting the need for future research to determine the impact of candidate mediators and moderators underlying these heterogeneous outcomes across evolving networks.

  3. User Participation and Honesty in Online Rating Systems: What a Social Network Can Do

    OpenAIRE

    Davoust, Alan; Esfandiari, Babak

    2016-01-01

    An important problem with online communities in general, and online rating systems in particular, is uncooperative behavior: lack of user participation, dishonest contributions. This may be due to an incentive structure akin to a Prisoners' Dilemma (PD). We show that introducing an explicit social network to PD games fosters cooperative behavior, and use this insight to design a new aggregation technique for online rating systems. Using a dataset of ratings from Yelp, we show that our aggrega...

  4. Support for Protests in Latin America: Classifications and the Role of Online Networking

    Directory of Open Access Journals (Sweden)

    Rachel R. Mourão

    2016-09-01

    Full Text Available In recent years, Latin Americans marched the streets in a wave of protests that swept almost every country in the region. Yet few studies have assessed how Latin Americans support various forms of protest, and how new technologies affect attitudes toward protest tactics. Using data from the Latin American Public Opinion Project (N = 37,102, cluster analyses grouped citizens into four distinct groups depending on their support for protests. Most Latin Americans support moderate forms of protest, rejecting more radical tactics. Online networking is associated with support for both moderate and radical protests. But those who support only moderate protests use online networking sites more than Latin Americans as a whole, while those who support radical protests use online networking sites significantly less. Our findings suggest that only peaceful and legal demonstrations have been normalized in the region, and online networking foments support for moderate protest tactics.

  5. Culture, Role and Group Work: A Social Network Analysis Perspective on an Online Collaborative Course

    Science.gov (United States)

    Stepanyan, Karen; Mather, Richard; Dalrymple, Roger

    2014-01-01

    This paper discusses the patterns of network dynamics within a multicultural online collaborative learning environment. It analyses the interaction of participants (both students and facilitators) within a discussion board that was established as part of a 3-month online collaborative course. The study employs longitudinal probabilistic social…

  6. Community (in) Colleges: The Relationship Between Online Network Involvement and Academic Outcomes at a Community College

    Science.gov (United States)

    Evans, Eliza D.; McFarland, Daniel A.; Rios-Aguilar, Cecilia; Deil-Amen, Regina

    2016-01-01

    Objective: This study explores the relationship between online social network involvement and academic outcomes among community college students. Prior theory hypothesizes that socio-academic moments are especially important for the integration of students into community colleges and that integration is related to academic outcomes. Online social…

  7. Social and Virtual Networks: Evaluating Synchronous Online Interviewing Using Instant Messenger

    Science.gov (United States)

    Hinchcliffe, Vanessa; Gavin, Helen

    2009-01-01

    This paper describes an evaluation of the quality and utility of synchronous online interviewing for data collection in social network research. Synchronous online interviews facilitated by Instant Messenger as the communication medium, were undertaken with ten final year university students. Quantitative and qualitative content analysis of…

  8. Three Eras in Global Tobacco Control: How Global Governance Processes Influenced Online Tobacco Control Networking.

    Science.gov (United States)

    Wipfli, Heather; Chu, Kar-Hai; Lancaster, Molly; Valente, Thomas

    2016-01-01

    Online networks can serve as a platform to diffuse policy innovations and enhance global health governance. This study focuses on how shifts in global health governance may influence related online networks. We compare social network metrics (average degree centrality [AVGD], density [D] and clustering coefficient [CC]) of Globalink, an online network of tobacco control advocates, across three eras in global tobacco control governance; pre-Framework Convention on Tobacco Control (FCTC) policy transfer (1992-1998), global regime formation through the FCTC negotiations (1999-2005), and philanthropic funding through the Bloomberg Initiative (2006-2012). Prior to 1999, Globalink was driven by a handful of high-income countries (AVGD=1.908 D=0.030, CC=0.215). The FCTC negotiations (1999-2005) corresponded with a rapid uptick in the number of countries represented within Globalink and new members were most often brought into the network through relationships with regional neighbors (AVGD=2.824, D=0.021, CC=0.253). Between 2006 and 2012, the centrality of the US in the network increases significantly (AVGD=3.414, D=0.023, CC=0.310). The findings suggest that global institutionalization through WHO, as with the FCTC, can lead to the rapid growth of decentralized online networks. Alternatively, private initiatives, such as the Bloomberg Initiative, can lead to clustering in which a single source of information gains increasing influence over an online network.

  9. Empirical analysis of online social networks in the age of Web 2.0

    Science.gov (United States)

    Fu, Feng; Liu, Lianghuan; Wang, Long

    2008-01-01

    Today the World Wide Web is undergoing a subtle but profound shift to Web 2.0, to become more of a social web. The use of collaborative technologies such as blogs and social networking site (SNS) leads to instant online community in which people communicate rapidly and conveniently with each other. Moreover, there are growing interest and concern regarding the topological structure of these new online social networks. In this paper, we present empirical analysis of statistical properties of two important Chinese online social networks-a blogging network and an SNS open to college students. They are both emerging in the age of Web 2.0. We demonstrate that both networks possess small-world and scale-free features already observed in real-world and artificial networks. In addition, we investigate the distribution of topological distance. Furthermore, we study the correlations between degree (in/out) and degree (in/out), clustering coefficient and degree, popularity (in terms of number of page views) and in-degree (for the blogging network), respectively. We find that the blogging network shows disassortative mixing pattern, whereas the SNS network is an assortative one. Our research may help us to elucidate the self-organizing structural characteristics of these online social networks embedded in technical forms.

  10. A sneak into the Devil's Colony - Fake Profiles in Online Social Networks

    OpenAIRE

    Wani, Mudasir Ahmad; Jabin, Suraiya

    2017-01-01

    Online Social Networks (OSNs) play an important role for internet users to carry out their daily activities like content sharing, news reading, posting messages, product reviews and discussing events etc. At the same time, various kinds of spammers are also equally attracted towards these OSNs. These cyber criminals including sexual predators, online fraudsters, advertising campaigners, catfishes, and social bots etc. exploit the network of trust by various means especially by creating fake p...

  11. The relationship between online social networking and depression : a systematic review of quantitative studies

    OpenAIRE

    Baker, David; Perez Algorta, Guillermo Daniel

    2016-01-01

    Online social networking sites (SNSs) such as Facebook, Twitter, and MySpace are used by billions of people every day to communicate and interact with others. There has been increasing interest in the potential impact of online social networking on wellbeing, with a broadening body of new research into factors associated with both positive and negative mental health outcomes such as depression. This systematic review of empirical studies (n=30) adds to existing research in this field by exami...

  12. Network affordances through online learning: Increasing use and complexity.

    OpenAIRE

    Hajhashemi, Karim; Anderson, Neil; Jackson, Cliff; Caltabiano, Nerina

    2013-01-01

    Computers, mobile devices and the Internet have enabled a learning environment described as online learning or a variety of other terms such as e-learning. Researchers believe that online learning has become more complex due to learners' sharing and acquiring knowledge at a variety of remote locations, in a variety of modalities. However, advances in technology and the integration of ICT with teaching and learning settings have quickened the growth of online learning and importantly have chan...

  13. Links between real and virtual networks: a comparative study of online communities in Japan and Korea.

    Science.gov (United States)

    Ishii, Kenichi; Ogasahara, Morihiro

    2007-04-01

    The present study explores how online communities affect real-world personal relations based on a cross-cultural survey conducted in Japan and Korea. Findings indicate that the gratifications of online communities moderate the effects of online communities on social participation. Online communities are categorized into a real-group-based community and a virtual-network-based community. The membership of real-group-based online community is positively correlated with social bonding gratification and negatively correlated with information- seeking gratification. Japanese users prefer more virtual-network-based online communities, while their Korean counterparts prefer real-group-based online communities. Korean users are more active in online communities and seek a higher level of socializing gratifications, such as social bonding and making new friends, when compared with their Japanese counterparts. These results indicate that in Korea, personal relations via the online community are closely associated with the real-world personal relations, but this is not the case in Japan. This study suggests that the effects of the Internet are culture-specific and that the online community can serve a different function in different cultural environments.

  14. Quantifying discrepancies in opinion spectra from online and offline networks.

    Science.gov (United States)

    Lee, Deokjae; Hahn, Kyu S; Yook, Soon-Hyung; Park, Juyong

    2015-01-01

    Online social media such as Twitter are widely used for mining public opinions and sentiments on various issues and topics. The sheer volume of the data generated and the eager adoption by the online-savvy public are helping to raise the profile of online media as a convenient source of news and public opinions on social and political issues as well. Due to the uncontrollable biases in the population who heavily use the media, however, it is often difficult to measure how accurately the online sphere reflects the offline world at large, undermining the usefulness of online media. One way of identifying and overcoming the online-offline discrepancies is to apply a common analytical and modeling framework to comparable data sets from online and offline sources and cross-analyzing the patterns found therein. In this paper we study the political spectra constructed from Twitter and from legislators' voting records as an example to demonstrate the potential limits of online media as the source for accurate public opinion mining, and how to overcome the limits by using offline data simultaneously.

  15. Quantifying discrepancies in opinion spectra from online and offline networks.

    Directory of Open Access Journals (Sweden)

    Deokjae Lee

    Full Text Available Online social media such as Twitter are widely used for mining public opinions and sentiments on various issues and topics. The sheer volume of the data generated and the eager adoption by the online-savvy public are helping to raise the profile of online media as a convenient source of news and public opinions on social and political issues as well. Due to the uncontrollable biases in the population who heavily use the media, however, it is often difficult to measure how accurately the online sphere reflects the offline world at large, undermining the usefulness of online media. One way of identifying and overcoming the online-offline discrepancies is to apply a common analytical and modeling framework to comparable data sets from online and offline sources and cross-analyzing the patterns found therein. In this paper we study the political spectra constructed from Twitter and from legislators' voting records as an example to demonstrate the potential limits of online media as the source for accurate public opinion mining, and how to overcome the limits by using offline data simultaneously.

  16. Preferential Attachment in Online Networks: Measurement and Explanations

    NARCIS (Netherlands)

    Kunegis, J; Blattner, M; Moser, C.

    2013-01-01

    We perform an empirical study of the preferential attachment phenomenon in temporal networks and show that on the Web, networks follow a nonlinear preferential attachment model in which the exponent depends on the type of network considered. The classical preferential attachment model for networks

  17. The Online Social Networking of Cyberspace: A Study on the Development of an Online Social Network Project and the Sport Industry's Perception of Its Relative Advantage

    Science.gov (United States)

    Liptrap, Timothy John

    2011-01-01

    This exploratory case study examined online social networking (OSN), and the perceptions of Sport Marketing students and sport industry professional as to the relative advantage of the OSN tools in the marketplace. The conceptual framework for this study was based on Boyer's (1990) concepts of Scholarship of Teaching and Learning (SoTL), and the…

  18. Online multistep-ahead inundation depth forecasts by recurrent NARX networks

    Directory of Open Access Journals (Sweden)

    H.-Y. Shen

    2013-03-01

    Full Text Available Various types of artificial neural networks (ANNs have been successfully applied in hydrological fields, but relatively scant on multistep-ahead flood inundation forecasting, which is very difficult to achieve, especially when dealing with forecasts without regular observed data. This study proposes a recurrent configuration of nonlinear autoregressive with exogenous inputs (NARX network, called R-NARX, to forecast multistep-ahead inundation depths in an inundation area. The proposed R-NARX is constructed based on the recurrent neural network (RNN, which is commonly used for modeling nonlinear dynamical systems. The models were trained and tested based on a large number of inundation data generated by a well validated two-dimensional simulation model at thirteen inundation-prone sites in Yilan County, Taiwan. We demonstrate that the R-NARX model can effectively inhibit error growth and accumulation when being applied to online multistep-ahead inundation forecasts over a long lasting forecast period. For comparison, a feedforward time-delay and an online feedback configuration of NARX networks (T-NARX and O-NARX were performed. The results show that (1 T-NARX networks cannot make online forecasts due to unavailable inputs in the constructed networks even though they provide the best performances for reference only; and (2 R-NARX networks consistently outperform O-NARX networks and can be adequately applied to online multistep-ahead forecasts of inundation depths in the study area during typhoon events.

  19. Toward Predicting Social Support Needs in Online Health Social Networks.

    Science.gov (United States)

    Choi, Min-Je; Kim, Sung-Hee; Lee, Sukwon; Kwon, Bum Chul; Yi, Ji Soo; Choo, Jaegul; Huh, Jina

    2017-08-02

    While online health social networks (OHSNs) serve as an effective platform for patients to fulfill their various social support needs, predicting the needs of users and providing tailored information remains a challenge. The objective of this study was to discriminate important features for identifying users' social support needs based on knowledge gathered from survey data. This study also provides guidelines for a technical framework, which can be used to predict users' social support needs based on raw data collected from OHSNs. We initially conducted a Web-based survey with 184 OHSN users. From this survey data, we extracted 34 features based on 5 categories: (1) demographics, (2) reading behavior, (3) posting behavior, (4) perceived roles in OHSNs, and (5) values sought in OHSNs. Features from the first 4 categories were used as variables for binary classification. For the prediction outcomes, we used features from the last category: the needs for emotional support, experience-based information, unconventional information, and medical facts. We compared 5 binary classifier algorithms: gradient boosting tree, random forest, decision tree, support vector machines, and logistic regression. We then calculated the scores of the area under the receiver operating characteristic (ROC) curve (AUC) to understand the comparative effectiveness of the used features. The best performance was AUC scores of 0.89 for predicting users seeking emotional support, 0.86 for experience-based information, 0.80 for unconventional information, and 0.83 for medical facts. With the gradient boosting tree as our best performing model, we analyzed the strength of individual features in predicting one's social support need. Among other discoveries, we found that users seeking emotional support tend to post more in OHSNs compared with others. We developed an initial framework for automatically predicting social support needs in OHSNs using survey data. Future work should involve nonsurvey

  20. Structural characteristics of the online social networks of maltreated youth and offline sexual risk behavior.

    Science.gov (United States)

    Negriff, Sonya; Valente, Thomas W

    2018-02-07

    Maltreated youth are at risk for exposure to online sexual content and high-risk sexual behavior, yet characteristics of their online social networks have not been examined as a potential source of vulnerability. The aims of the current study were: 1) to test indicators of size (number of friends) and fragmentation (number of connections between friends) of maltreated young adults' online networks as predictors of intentional and unintentional exposure to sexual content and offline high-risk sexual behavior and 2) to test maltreatment as a moderator of these associations. Participants were selected from a longitudinal study on the effects of child maltreatment (n = 152; Mean age 21.84 years). Data downloaded from Facebook were used to calculate network variables of size (number of friends), density (connections between friends), average degree (average number of connections for each friend), and percent isolates (those not connected to others in the network). Self-reports of intentional and unintentional exposure to online sexual content and offline high-risk sexual behavior were the outcome variables. Multiple-group path modeling showed that only for the maltreated group having a higher percent of isolates in the network predicted intentional exposure to online sexual content and offline high-risk sexual behavior. An implication of this finding is that the composition of the Facebook network may be used as a risk indicator for individuals with child-welfare documented maltreatment experiences. Copyright © 2018. Published by Elsevier Ltd.

  1. Gender differences in collaborative learning over online social networks: Epistemological beliefs and behaviors

    Directory of Open Access Journals (Sweden)

    Rosanna Y.-Y. Chan

    2013-09-01

    Full Text Available Online social networks are popular venues for computer-supported collaborative work and computer-supported collaborative learning. Professionals within the same discipline, such as software developers, often interact over various social network sites for knowledge updates and collective understandings. The current study aims at gathering empirical evidences concerning gender differences in online social network beliefs and behaviors. A total of 53 engineering postgraduate students were engaged in a blogging community for collaborative learning. Participants’ beliefs about collaboration and nature of knowledge and knowing (i.e. epistemological beliefs are investigated. More specifically, social network analysis metrics including in-degree, out-degree, closeness centrality, and betweenness centrality are obtained from an 8-interval longitudinal SNA. Methodologically speaking, the current work puts forward mixed methods of longitudinal SNA and quantitative beliefs survey to explore online social network participants’ beliefs and behaviors. The study’s findings demonstrate significant gender differences in collaborative learning through online social networks, including (1 female engineering postgraduate students engage significantly more actively in online communications, (2 male engineering postgraduate students are more likely to be the potential controllers of information flows, and (3 gender differences exist in belief gains related to social aspects, but not individual's epistemic aspects. Overall, participants in both genders demonstrated enhanced beliefs in collaboration as well as the nature of knowledge and knowing.

  2. Boundedness and convergence of online gradient method with penalty for feedforward neural networks.

    Science.gov (United States)

    Zhang, Huisheng; Wu, Wei; Liu, Fei; Yao, Mingchen

    2009-06-01

    In this brief, we consider an online gradient method with penalty for training feedforward neural networks. Specifically, the penalty is a term proportional to the norm of the weights. Its roles in the method are to control the magnitude of the weights and to improve the generalization performance of the network. By proving that the weights are automatically bounded in the network training with penalty, we simplify the conditions that are required for convergence of online gradient method in literature. A numerical example is given to support the theoretical analysis.

  3. Online Social Networking, Sexual Risk and Protective Behaviors: Considerations for Clinicians and Researchers.

    Science.gov (United States)

    Holloway, Ian W; Dunlap, Shannon; Del Pino, Homero E; Hermanstyne, Keith; Pulsipher, Craig; Landovitz, Raphael J

    2014-09-01

    Online social networking refers to the use of internet-based technologies that facilitate connection and communication between users. These platforms may be accessed via computer or mobile device (e.g., tablet, smartphone); communication between users may include linking of profiles, posting of text, photo and video content, instant messaging and email. This review provides an overview of recent research on the relationship between online social networking and sexual risk and protective behaviors with a focus on use of social networking sites (SNS) among young people and populations at high risk for sexually transmitted infections (STIs). While findings are mixed, the widespread use of SNS for sexual communication and partner seeking presents opportunities for the delivery and evaluation of public health interventions. Results of SNS-based interventions to reduce sexual risk are synthesized in order to offer hands-on advice for clinicians and researchers interested in engaging patients and study participants via online social networking.

  4. Social networks and online environments: when science and practice co-evolve

    OpenAIRE

    Rosen, Devan; Barnett, George A.; Kim, Jang Hyun

    2011-01-01

    The science of social network analysis has co-evolved with the development of online environments and computer-mediated communication. Unique and precise data available from computer and information systems have allowed network scientists to explore novel social phenomena and develop new methods. Additionally, advances in the structural analysis and visualization of computer-mediated social networks have informed developers and shaped the design of social media tools. This article reviews som...

  5. Habit as a moderator and exogenous predictor of social networks: The case of online social networking

    Directory of Open Access Journals (Sweden)

    Akwesi Assensoh-Kodua

    2015-10-01

    Full Text Available This paper tests the factors likely to impact continuance intentions through the medium of online social networks (OSN for business transactions. The expectation-confirmation theory (ECT from the consumer behaviour literature is made use of; to forward a set of theories that validate a prior model from IS usage research. Eight research hypotheses, after a field survey of OSNs participants for business transactions were conducted are empirically validated. 300 useable responses from LinkedIn and Twitter social networking platforms users for business transactions were analysed with the WarpPLS 4.0 bootstrapping technique. The study results provide significant evidence in support of perceived trust and user satisfaction, as determinants of the continuance intention of people using OSN platforms for business transactions. Above all, the research model was tested for the moderating effects of usage habit, which was found to impact relationships between continuance intention and perceived trust, resulting in an improved predictive capability of (R2=0.55 as compared to base model of (R2=0.52. The moderating result indicates that a higher level of habit increases the effect of perceived trust on continuance intention

  6. Multi-Stratum Networks: toward a unified model of on-line identities

    DEFF Research Database (Denmark)

    Rossi, Luca; Magnani, Matteo

    2012-01-01

    One of the reasons behind the success of Social Network Analysis is its simple and general graph model made of nodes (representing individuals) and ties. However, when we focus on our daily on-line experience we must confront a more complex scenario: people inhabitate several on-line spaces...... interacting to several communities active on various technological infrastructures like Twitter, Facebook, YouTube or FourSquare and with distinct social objectives. This constitutes a complex network of interconnected networks where users' identities are spread and where information propagates navigating...... through different communities and social platforms. In this article we introduce a model for this layered scenario that we call multi-stratum network. Through a theoretical discussion and the analysis of real-world data we show how not only focusing on a single network may provide a very partial...

  7. Tweacher: New proposal for Online Social Networks Impact in Secondary Education

    Directory of Open Access Journals (Sweden)

    Sebastián ROMERO

    2013-05-01

    Full Text Available This paper presents and analyzes the potential uses and motivations of online social networks in education, with special emphasis on secondary education. First, we show several previous researches supporting the use of social networking as an educational tool and discuss Edmodo, an educative online social network. The work carried out during two academic years with senior students of primary and secondary schools is also analyzed. After that we present Tweacher an educative social network application and evaluate its use in the classroom to prove its useful use between teachers and students. This research has allowed us to see the reality of social network use among young people and identify the challenges of its application to education environment.

  8. Developing an online professional network for veterinary education: the NOVICE project.

    Science.gov (United States)

    Baillie, Sarah; Kinnison, Tierney; Forrest, Neil; Dale, Vicki H M; Ehlers, Jan P; Koch, Michael; Mándoki, Mira; Ciobotaru, Emilia; de Groot, Esther; Boerboom, Tobias B B; van Beukelen, Peter

    2011-01-01

    An online professional network for veterinarians, veterinary students, veterinary educationalists, and ICT (Information and Communication Technology) educationalists is being developed under the EU (European Union) Lifelong Learning Programme. The network uses Web 2.0, a term used to describe the new, more interactive version of the Internet, and includes tools such as wikis, blogs, and discussion boards. Focus groups conducted with qualified and student veterinarians within the project's five founding countries (The Netherlands, Germany, United Kingdom, Hungary, Romania) demonstrated that online professional communities can be valuable for accessing information and establishing contacts. Online networks have the potential to overcome common challenges to face-to-face communities-such as distance, cost, and timing-but they have their own drawbacks, such as security and professionalism issues. The Network Of Veterinary ICt in Education (NOVICE) was developed using Elgg, an open-source, free social networking platform, after several software options had been considered. NOVICE aims to promote the understanding of Web 2.0, confidence to use social software tools, and participation in an online community. Therefore, the Web site contains help sections, Frequently Asked Questions, and access to support from ICT experts. Five months after the network's launch (and just over one year into the project) 515 members from 28 countries had registered. Further research will include analysis of a core group's activities, which will inform ongoing support for and development of informal, lifelong learning in a veterinary context.

  9. Do online social media cut through the constraints that limit the size of offline social networks?

    Science.gov (United States)

    Dunbar, R I M

    2016-01-01

    The social brain hypothesis has suggested that natural social network sizes may have a characteristic size in humans. This is determined in part by cognitive constraints and in part by the time costs of servicing relationships. Online social networking offers the potential to break through the glass ceiling imposed by at least the second of these, potentially enabling us to maintain much larger social networks. This is tested using two separate UK surveys, each randomly stratified by age, gender and regional population size. The data show that the size and range of online egocentric social networks, indexed as the number of Facebook friends, is similar to that of offline face-to-face networks. For one sample, respondents also specified the number of individuals in the inner layers of their network (formally identified as support clique and sympathy group), and these were also similar in size to those observed in offline networks. This suggests that, as originally proposed by the social brain hypothesis, there is a cognitive constraint on the size of social networks that even the communication advantages of online media are unable to overcome. In practical terms, it may reflect the fact that real (as opposed to casual) relationships require at least occasional face-to-face interaction to maintain them.

  10. Online Social Networking among students and its impact on Marketing - The Case of YouTube

    OpenAIRE

    Sahgal, Shaira

    2008-01-01

    ABSTRACT The literature on online social networking and the use of the internet for socialising purposes by adolescents and youngsters today is fairly recent and there does not seem to be much existing research on the topic barring the few. This study aims to try and fill that gap through interviews conducted among university students and understanding the reasons behind their preference for such online means of communicating and broadcasting as opposed to traditional offline methods like...

  11. Towards benchmarking citizen observatories: Features and functioning of online amateur weather networks.

    Science.gov (United States)

    Gharesifard, Mohammad; Wehn, Uta; van der Zaag, Pieter

    2017-05-15

    Crowd-sourced environmental observations are increasingly being considered as having the potential to enhance the spatial and temporal resolution of current data streams from terrestrial and areal sensors. The rapid diffusion of ICTs during the past decades has facilitated the process of data collection and sharing by the general public and has resulted in the formation of various online environmental citizen observatory networks. Online amateur weather networks are a particular example of such ICT-mediated observatories that are rooted in one of the oldest and most widely practiced citizen science activities, namely amateur weather observation. The objective of this paper is to introduce a conceptual framework that enables a systematic review of the features and functioning of these expanding networks. This is done by considering distinct dimensions, namely the geographic scope and types of participants, the network's establishment mechanism, revenue stream(s), existing communication paradigm, efforts required by data sharers, support offered by platform providers, and issues such as data accessibility, availability and quality. An in-depth understanding of these dimensions helps to analyze various dynamics such as interactions between different stakeholders, motivations to run the networks, and their sustainability. This framework is then utilized to perform a critical review of six existing online amateur weather networks based on publicly available data. The main findings of this analysis suggest that: (1) there are several key stakeholders such as emergency services and local authorities that are not (yet) engaged in these networks; (2) the revenue stream(s) of online amateur weather networks is one of the least discussed but arguably most important dimensions that is crucial for the sustainability of these networks; and (3) all of the networks included in this study have one or more explicit modes of bi-directional communication, however, this is limited to

  12. Designing for Learning: Online Social Networks as a Classroom Environment

    Science.gov (United States)

    Casey, Gail; Evans, Terry

    2011-01-01

    This paper deploys notions of emergence, connections, and designs for learning to conceptualize high school students' interactions when using online social media as a learning environment. It makes links to chaos and complexity theories and to fractal patterns as it reports on a part of the first author's action research study, conducted while she…

  13. Online Social Networks: Essays on Membership, Privacy, and Structure

    NARCIS (Netherlands)

    Hofstra, B.

    2017-01-01

    The structure of social networks is crucial for obtaining social support, for meaningful connections to unknown social groups, and to overcome prejudice. Yet, we know little about the structure of social networks beyond those contacts that stand closest to us. This lack of knowledge results from a

  14. Towards a Social Networks Model for Online Learning & Performance

    Science.gov (United States)

    Chung, Kon Shing Kenneth; Paredes, Walter Christian

    2015-01-01

    In this study, we develop a theoretical model to investigate the association between social network properties, "content richness" (CR) in academic learning discourse, and performance. CR is the extent to which one contributes content that is meaningful, insightful and constructive to aid learning and by social network properties we…

  15. Craving Facebook? Behavioral addiction to online social networking and its association with emotion regulation deficits.

    Science.gov (United States)

    Hormes, Julia M; Kearns, Brianna; Timko, C Alix

    2014-12-01

    To assess disordered online social networking use via modified diagnostic criteria for substance dependence, and to examine its association with difficulties with emotion regulation and substance use. Cross-sectional survey study targeting undergraduate students. Associations between disordered online social networking use, internet addiction, deficits in emotion regulation and alcohol use problems were examined using univariate and multivariate analyses of covariance. A large University in the Northeastern United States. Undergraduate students (n = 253, 62.8% female, 60.9% white, age mean = 19.68, standard deviation = 2.85), largely representative of the target population. The response rate was 100%. Disordered online social networking use, determined via modified measures of alcohol abuse and dependence, including DSM-IV-TR diagnostic criteria for alcohol dependence, the Penn Alcohol Craving Scale and the Cut-down, Annoyed, Guilt, Eye-opener (CAGE) screen, along with the Young Internet Addiction Test, Alcohol Use Disorders Identification Test, Acceptance and Action Questionnaire-II, White Bear Suppression Inventory and Difficulties in Emotion Regulation Scale. Disordered online social networking use was present in 9.7% [n = 23; 95% confidence interval (5.9, 13.4)] of the sample surveyed, and significantly and positively associated with scores on the Young Internet Addiction Test (P addictive. Modified measures of substance abuse and dependence are suitable in assessing disordered online social networking use. Disordered online social networking use seems to arise as part of a cluster of symptoms of poor emotion regulation skills and heightened susceptibility to both substance and non-substance addiction. © 2014 Society for the Study of Addiction.

  16. Online Adaboost-Based Parameterized Methods for Dynamic Distributed Network Intrusion Detection.

    Science.gov (United States)

    Hu, Weiming; Gao, Jun; Wang, Yanguo; Wu, Ou; Maybank, Stephen

    2014-01-01

    Current network intrusion detection systems lack adaptability to the frequently changing network environments. Furthermore, intrusion detection in the new distributed architectures is now a major requirement. In this paper, we propose two online Adaboost-based intrusion detection algorithms. In the first algorithm, a traditional online Adaboost process is used where decision stumps are used as weak classifiers. In the second algorithm, an improved online Adaboost process is proposed, and online Gaussian mixture models (GMMs) are used as weak classifiers. We further propose a distributed intrusion detection framework, in which a local parameterized detection model is constructed in each node using the online Adaboost algorithm. A global detection model is constructed in each node by combining the local parametric models using a small number of samples in the node. This combination is achieved using an algorithm based on particle swarm optimization (PSO) and support vector machines. The global model in each node is used to detect intrusions. Experimental results show that the improved online Adaboost process with GMMs obtains a higher detection rate and a lower false alarm rate than the traditional online Adaboost process that uses decision stumps. Both the algorithms outperform existing intrusion detection algorithms. It is also shown that our PSO, and SVM-based algorithm effectively combines the local detection models into the global model in each node; the global model in a node can handle the intrusion types that are found in other nodes, without sharing the samples of these intrusion types.

  17. Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

    Science.gov (United States)

    Hageman, Jacob J.; Smith, Mark S.; Stachowiak, Susan

    2003-01-01

    An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.

  18. On-line identification of hybrid systems using an adaptive growing and pruning RBF neural network

    DEFF Research Database (Denmark)

    Alizadeh, Tohid

    2008-01-01

    This paper introduces an adaptive growing and pruning radial basis function (GAP-RBF) neural network for on-line identification of hybrid systems. The main idea is to identify a global nonlinear model that can predict the continuous outputs of hybrid systems. In the proposed approach, GAP......-RBF neural network uses a modified unscented kalman filter (UKF) with forgetting factor scheme as the required on-line learning algorithm. The effectiveness of the resulting identification approach is tested and evaluated on a simulated benchmark hybrid system....

  19. Disseminating Innovations in Teaching Value-Based Care Through an Online Learning Network.

    Science.gov (United States)

    Gupta, Reshma; Shah, Neel T; Moriates, Christopher; Wallingford, September; Arora, Vineet M

    2017-08-01

    A national imperative to provide value-based care requires new strategies to teach clinicians about high-value care. We developed a virtual online learning network aimed at disseminating emerging strategies in teaching value-based care. The online Teaching Value in Health Care Learning Network includes monthly webinars that feature selected innovators, online discussion forums, and a repository for sharing tools. The learning network comprises clinician-educators and health system leaders across North America. We conducted a cross-sectional online survey of all webinar presenters and the active members of the network, and we assessed program feasibility. Six months after the program launched, there were 277 learning community members in 22 US states. Of the 74 active members, 50 (68%) completed the evaluation. Active members represented independently practicing physicians and trainees in 7 specialties, nurses, educators, and health system leaders. Nearly all speakers reported that the learning network provided them with a unique opportunity to connect with a different audience and achieve greater recognition for their work. Of the members who were active in the learning network, most reported that strategies gleaned from the network were helpful, and some adopted or adapted these innovations at their home institutions. One year after the program launched, the learning network had grown to 364 total members. The learning network helped participants share and implement innovations to promote high-value care. The model can help disseminate innovations in emerging areas of health care transformation, and is sustainable without ongoing support after a period of start-up funding.

  20. Limitation of degree information for analyzing the interaction evolution in online social networks

    Science.gov (United States)

    Shang, Ke-Ke; Yan, Wei-Sheng; Xu, Xiao-Ke

    2014-04-01

    Previously many studies on online social networks simply analyze the static topology in which the friend relationship once established, then the links and nodes will not disappear, but this kind of static topology may not accurately reflect temporal interactions on online social services. In this study, we define four types of users and interactions in the interaction (dynamic) network. We found that active, disappeared, new and super nodes (users) have obviously different strength distribution properties and this result also can be revealed by the degree characteristics of the unweighted interaction and friendship (static) networks. However, the active, disappeared, new and super links (interactions) only can be reflected by the strength distribution in the weighted interaction network. This result indicates the limitation of the static topology data on analyzing social network evolutions. In addition, our study uncovers the approximately stable statistics for the dynamic social network in which there are a large variation for users and interaction intensity. Our findings not only verify the correctness of our definitions, but also helped to study the customer churn and evaluate the commercial value of valuable customers in online social networks.

  1. Online fouling detection in electrical circulation heaters using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Lalot, S. [M.E.T.I.E.R., Longuenesse Cedex (France); Universite de Valenciennes (France). LME; Lecoeuche, S. [M.E.T.I.E.R., Longuenesse Cedex (France); Universite de Lille (France). Laboratoire 13D

    2003-06-01

    Here is presented a method that is able to detect fouling during the service of a circulation electrical heater. The neural based technique is divided in two major steps: identification and classification. Each step uses a neural network, the connection weights of the first one being the inputs of the second network. Each step is detailed and the main characteristics and abilities of the two neural networks are given. It is shown that the method is able to discriminate fouling from viscosity modification that would lead to the same type of effect on the total heat transfer coefficient. (author)

  2. Identification of influential users by neighbors in online social networks

    Science.gov (United States)

    Sheikhahmadi, Amir; Nematbakhsh, Mohammad Ali; Zareie, Ahmad

    2017-11-01

    Identification and ranking of influential users in social networks for the sake of news spreading and advertising has recently become an attractive field of research. Given the large number of users in social networks and also the various relations that exist among them, providing an effective method to identify influential users has been gradually considered as an essential factor. In most of the already-provided methods, those users who are located in an appropriate structural position of the network are regarded as influential users. These methods do not usually pay attention to the interactions among users, and also consider those relations as being binary in nature. This paper, therefore, proposes a new method to identify influential users in a social network by considering those interactions that exist among the users. Since users tend to act within the frame of communities, the network is initially divided into different communities. Then the amount of interaction among users is used as a parameter to set the weight of relations existing within the network. Afterward, by determining the neighbors' role for each user, a two-level method is proposed for both detecting users' influence and also ranking them. Simulation and experimental results on twitter data shows that those users who are selected by the proposed method, comparing to other existing ones, are distributed in a more appropriate distance. Moreover, the proposed method outperforms the other ones in terms of both the influential speed and capacity of the users it selects.

  3. Simulating Social Networks of Online Communities: Simulation as a Method for Sociability Design

    Science.gov (United States)

    Ang, Chee Siang; Zaphiris, Panayiotis

    We propose the use of social simulations to study and support the design of online communities. In this paper, we developed an Agent-Based Model (ABM) to simulate and study the formation of social networks in a Massively Multiplayer Online Role Playing Game (MMORPG) guild community. We first analyzed the activities and the social network (who-interacts-with-whom) of an existing guild community to identify its interaction patterns and characteristics. Then, based on the empirical results, we derived and formalized the interaction rules, which were implemented in our simulation. Using the simulation, we reproduced the observed social network of the guild community as a means of validation. The simulation was then used to examine how various parameters of the community (e.g. the level of activity, the number of neighbors of each agent, etc) could potentially influence the characteristic of the social networks.

  4. Users structure and behavior on an online social network during a political protest

    Science.gov (United States)

    Morales, A. J.; Losada, J. C.; Benito, R. M.

    2012-11-01

    Over the past years, new technologies and specially online social networks have penetrated into the world’s population at an accelerated pace. In this paper we analyze collected data from the web application Twitter, in order to describe the structure and dynamics of the emergent social networks, based on complexity science. We focused on a Venezuelan protest that took place exclusively by Twitter during December, 2010. We found a community structure with highly connected hubs and three different kinds of user behavior that determine the information flow dynamics. We noticed that even though online social networks appear to be a pure social environment, traditional media still holds loads of influence inside the network.

  5. Communication, opponents, and clan performance in online games: a social network approach.

    Science.gov (United States)

    Lee, Hong Joo; Choi, Jaewon; Kim, Jong Woo; Park, Sung Joo; Gloor, Peter

    2013-12-01

    Online gamers form clans voluntarily to play together and to discuss their real and virtual lives. Although these clans have diverse goals, they seek to increase their rank in the game community by winning more battles. Communications among clan members and battles with other clans may influence the performance of a clan. In this study, we compared the effects of communication structure inside a clan, and battle networks among clans, with the performance of the clans. We collected battle histories, posts, and comments on clan pages from a Korean online game, and measured social network indices for communication and battle networks. Communication structures in terms of density and group degree centralization index had no significant association with clan performance. However, the centrality of clans in the battle network was positively related to the performance of the clan. If a clan had many battle opponents, the performance of the clan improved.

  6. Adaptive control of nonlinear system using online error minimum neural networks.

    Science.gov (United States)

    Jia, Chao; Li, Xiaoli; Wang, Kang; Ding, Dawei

    2016-11-01

    In this paper, a new learning algorithm named OEM-ELM (Online Error Minimized-ELM) is proposed based on ELM (Extreme Learning Machine) neural network algorithm and the spreading of its main structure. The core idea of this OEM-ELM algorithm is: online learning, evaluation of network performance, and increasing of the number of hidden nodes. It combines the advantages of OS-ELM and EM-ELM, which can improve the capability of identification and avoid the redundancy of networks. The adaptive control based on the proposed algorithm OEM-ELM is set up which has stronger adaptive capability to the change of environment. The adaptive control of chemical process Continuous Stirred Tank Reactor (CSTR) is also given for application. The simulation results show that the proposed algorithm with respect to the traditional ELM algorithm can avoid network redundancy and improve the control performance greatly. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  7. Human-Centered Development of an Online Social Network for Metabolic Syndrome Management.

    Science.gov (United States)

    Núñez-Nava, Jefersson; Orozco-Sánchez, Paola A; López, Diego M; Ceron, Jesus D; Alvarez-Rosero, Rosa E

    2016-01-01

    According to the International Diabetes Federation (IDF), a quarter of the world's population has Metabolic Syndrome (MS). To develop (and assess the users' degree of satisfaction of) an online social network for patients who suffer from Metabolic Syndrome, based on the recommendations and requirements of the Human-Centered Design. Following the recommendations of the ISO 9241-210 for Human-Centered Design (HCD), an online social network was designed to promote physical activity and healthy nutrition. In order to guarantee the active participation of the users during the development of the social network, a survey, an in-depth interview, a focal group, and usability tests were carried out with people suffering from MS. The study demonstrated how the different activities, recommendations, and requirements of the ISO 9241-210 are integrated into a traditional software development process. Early usability tests demonstrated that the user's acceptance and the effectiveness and efficiency of the social network are satisfactory.

  8. On-line thermal margin estimation of a PWR core using a neural network approach

    International Nuclear Information System (INIS)

    Park, Soon Ok; Kim, Hyun Koon; Lee, Seung Hynk; Chang, Soon Heung

    1992-01-01

    A new approach for on-line thermal margin monitoring of a PWR Core is proposed in this paper, where a neural network model is introduced to predict the DNBR values at the given reactor operating conditions. The neural network is learned by the Back Propagation algorithm with the optimized random training data and is tested to investigate the generalized performance for the steady state operating region as well as for the transient situations where DNB is of the primary concern. The test results show that the high level of accuracy in predicting the DNBR can be achieved by the neural network model compared to the detailed code results. An insight has been gained from this study that the neural network model for estimating DNB performance can be a viable tool for on-line thermal margin monitoring of a nuclear power plant

  9. Online solving of economic dispatch problem using neural network approach and comparing it with classical method

    International Nuclear Information System (INIS)

    Mohammadi, A.; Varahram, M.H.

    2007-01-01

    In this study, two methods for solving economic dispatch problems, namely Hopfield neural network and lambda iteration method are compared. Three sample of power system with 3, 6 and 20 units have been considered. The time required for CPU, for solving economic dispatch of these two systems has been calculated. It has been Shown that for on-line economic dispatch, Hopfield neural network is more efficient and the time required for Convergence is considerably smaller compared to classical methods. (author)

  10. Online Signature Verification using Recurrent Neural Network and Length-normalized Path Signature

    OpenAIRE

    Lai, Songxuan; Jin, Lianwen; Yang, Weixin

    2017-01-01

    Inspired by the great success of recurrent neural networks (RNNs) in sequential modeling, we introduce a novel RNN system to improve the performance of online signature verification. The training objective is to directly minimize intra-class variations and to push the distances between skilled forgeries and genuine samples above a given threshold. By back-propagating the training signals, our RNN network produced discriminative features with desired metrics. Additionally, we propose a novel d...

  11. Making "social" safer: are Facebook and other online networks becoming less hazardous for health professionals?

    Science.gov (United States)

    George, Daniel R

    2012-01-01

    Major concerns about privacy have limited health professionals' usage of popular social networking sites such as Facebook. However, the landscape of social media is changing in favor of more sophisticated privacy controls that enable users to more carefully manage public and private information. This evolution in technology makes it potentially less hazardous for health professionals to consider accepting colleagues and patients into their online networks, and invites medicine to think constructively about how social media may add value to contemporary healthcare.

  12. Online and in-person networking among women in the Earth Sciences Women's Network at www.ESWNonline.org

    Science.gov (United States)

    Kontak, R.; Adams, A. S.; De Boer, A. M.; Hastings, M. G.; Holloway, T.; Marin-Spiotta, E.; Steiner, A. L.; Wiedinmyer, C.

    2012-12-01

    The Earth Science Women's Network is an international peer-mentoring network of women in the Earth Sciences, many of whom are in the early stages of their careers. Membership is free and has grown through "word of mouth," and includes upper-level undergraduates, graduate students, professionals in a range of environmental fields, scientists working in public and private institutions. Our mission is to promote career development, build community, provide informal mentoring and support, and facilitate professional collaborations. Since 2002 we have accomplished this trough online networking, including over email and a listserv, on facebook, in-person networking events, and professional development workshops. Now in our 10th year, ESWN is debuting a new web-center that creates an online space exclusively for women in any discipline of the Earth (including planetary) sciences. ESWN members can connect and create an online community of support and encouragement for themselves as women in a demanding career. Many women in Earth Science fields feel isolated and are often the only woman in their department or work environments. ESWN is a place to meet others, discuss issues faced in creating work-life balance and professional success and share best practices through peer mentoring. Now on ESWN's new web-center, members can create and personalize their profiles and search for others in their field, nearby, or with similar interests. Online discussions in the members-only area can also be searched. Members can create groups for discussion or collaboration, with document sharing and password protection. Publicly, we can share gained knowledge with a broader audience, like lessons learned at our professional development workshops and collected recommendations from members. The new web center allows for more connectivity among other online platforms used by our members, including linked-in, facebook, and twitter. Built in Wordpress with a Buddpress members-only section, the new

  13. Suicide ideation of individuals in online social networks.

    Directory of Open Access Journals (Sweden)

    Naoki Masuda

    Full Text Available Suicide explains the largest number of death tolls among Japanese adolescents in their twenties and thirties. Suicide is also a major cause of death for adolescents in many other countries. Although social isolation has been implicated to influence the tendency to suicidal behavior, the impact of social isolation on suicide in the context of explicit social networks of individuals is scarcely explored. To address this question, we examined a large data set obtained from a social networking service dominant in Japan. The social network is composed of a set of friendship ties between pairs of users created by mutual endorsement. We carried out the logistic regression to identify users' characteristics, both related and unrelated to social networks, which contribute to suicide ideation. We defined suicide ideation of a user as the membership to at least one active user-defined community related to suicide. We found that the number of communities to which a user belongs to, the intransitivity (i.e., paucity of triangles including the user, and the fraction of suicidal neighbors in the social network, contributed the most to suicide ideation in this order. Other characteristics including the age and gender contributed little to suicide ideation. We also found qualitatively the same results for depressive symptoms.

  14. Suicide ideation of individuals in online social networks.

    Science.gov (United States)

    Masuda, Naoki; Kurahashi, Issei; Onari, Hiroko

    2013-01-01

    Suicide explains the largest number of death tolls among Japanese adolescents in their twenties and thirties. Suicide is also a major cause of death for adolescents in many other countries. Although social isolation has been implicated to influence the tendency to suicidal behavior, the impact of social isolation on suicide in the context of explicit social networks of individuals is scarcely explored. To address this question, we examined a large data set obtained from a social networking service dominant in Japan. The social network is composed of a set of friendship ties between pairs of users created by mutual endorsement. We carried out the logistic regression to identify users' characteristics, both related and unrelated to social networks, which contribute to suicide ideation. We defined suicide ideation of a user as the membership to at least one active user-defined community related to suicide. We found that the number of communities to which a user belongs to, the intransitivity (i.e., paucity of triangles including the user), and the fraction of suicidal neighbors in the social network, contributed the most to suicide ideation in this order. Other characteristics including the age and gender contributed little to suicide ideation. We also found qualitatively the same results for depressive symptoms.

  15. An information search model for online social Networks - MOBIRSE

    OpenAIRE

    Miguel Angel Niño Zambrano; Iván Darío Cerón Moreno; Jhon Alberto Astaiza Perafán; Gustavo Adolfo Ramírez

    2015-01-01

    En los últimos años las Redes Sociales Online (RSO) han venido cobrando gran importancia entre los usuarios de Internet, puesto que son sitios donde se puede conocer personas, publicar y compartir contenidos de una manera fácil y gratuita. Esto ha provocado que el volumen de información contenida en estos sitios web crezca de manera exponencial. Por lo tanto, la búsqueda web se convierte en una herramienta importante para que los usuarios puedan encontrar fácilmente la información relevante p...

  16. Frequency of victimization experiences and well-being among online, offline and combined victims on social online network sites of German children and adolescents

    Directory of Open Access Journals (Sweden)

    Michael eGlüer

    2015-12-01

    Full Text Available Victimization is associated with negative developmental outcomes in childhood and adolescence. However, previous studies have provided mixed results regarding the association between offline and online victimization and indicators of social, psychological, and somatic well-being. In this study, we investigated 1,906 German children and adolescents (grades 5 to 10, mean age = 13.9; SD = 2.1 with and without offline or online victimization experiences who participated in a social online network (SNS. Online questionnaires were used to assess previous victimization (offline, online, combined, and without, somatic and psychological symptoms, self-esteem, and social self-concept (social competence, resistance to peer influence, esteem by others. In total, 1,362 (71.4% children and adolescents reported being a member of at least one social online network, and 377 students (28.8% reported previous victimization. Most children and adolescents had offline victimization experiences (17.5%, whereas 2.7% reported online victimization, and 8.6% reported combined experiences. Girls reported more online and combined victimization, and boys reported more offline victimization. The type of victimization (offline, online, combined was associated with increased reports of psychological and somatic symptoms, lower self-esteem and esteem by others, and lower resistance to peer influences. The effects were comparable for the groups with offline and online victimization. They were, however, increased in the combined group in comparison to victims with offline experiences alone.

  17. Technology use and reasons to participate in online social networking websites for people living with HIV in the US

    Science.gov (United States)

    Horvath, Keith J.; Danilenko, Gene P.; Williams, Mark L.; Simoni, Jane; Amico, K. Rivet; Oakes, J. Michael; Rosser, B.R. Simon

    2012-01-01

    It is unknown if online social networking technologies are already highly integrated among some people living with HIV (PLWH) or have yet to be adopted. To fill this gap in understanding, 312 PLWH (84% male, 69% white) residing in the US completed on online survey in 2009 of their patterns of social networking and mobile phone use. Twenty-two persons also participated in one of two online focus groups. Results showed that 76% of participants with lower adherence to HIV medication used social networking websites/features at least once a week. Their ideal online social networking health websites included one that facilitated socializing with others (45% of participants) and relevant informational content (22%), although privacy was a barrier to use (26%). Texting (81%), and to a lesser extent mobile web-access (51%), was widely used among participants. Results support the potential reach of online social networking and text messaging intervention approaches. PMID:22350832

  18. Analysis of Online Social Networks to Understand Information Sharing Behaviors Through Social Cognitive Theory.

    Science.gov (United States)

    Yoon, Hong-Jun; Tourassi, Georgia

    2014-05-01

    Analyzing the contents of online social networks is an effective process for monitoring and understanding peoples' behaviors. Since the nature of conversation and information propagation is similar to traditional conversation and learning, one of the popular socio-cognitive methods, social cognitive theory was applied to online social networks to. Two major news topics about colon cancer were chosen to monitor traffic of Twitter messages. The activity of "leaders" on the issue (i.e., news companies or people will prior Twitter activity on topics related to colon cancer) was monitored. In addition, the activity of "followers", people who never discussed the topics before, but replied to the discussions was also monitored. Topics that produce tangible benefits such as positive outcomes from appropriate preventive actions received dramatically more attention and online social media traffic. Such characteristics can be explained with social cognitive theory and thus present opportunities for effective health campaigns.

  19. Usefulness of Social Network Sites for Adolescents' Development of Online Career Skills

    NARCIS (Netherlands)

    Rutten, Mariëlle; Ros, Anje; Kuijpers, Marinka; Kreijns, Karel

    2018-01-01

    Schools have an important role in teaching students how to use Social Network Site (SNS) for career purposes. This involves the opportunity for students to practice online career skills. Different types of digital environments are available for schools. There are SNS designed to enable users to

  20. Getting acquainted through social networking sites: testing a model of online uncertainty reduction and social attraction

    NARCIS (Netherlands)

    Antheunis, M.L.; Valkenburg, P.M.; Peter, J.

    2010-01-01

    The first aim of this study was to examine which uncertainty reduction strategies members of social network sites used to gain information about a person who they had recently met online. The second aim was to investigate whether and how these uncertainty reduction strategies resulted in social

  1. Getting acquainted through social networking sites: Testing a model of online uncertainty reduction and social attraction

    NARCIS (Netherlands)

    Antheunis, M.L.; Valkenburg, P.M.; Peter, J.

    2008-01-01

    The first aim of this study was to examine which uncertainty reduction strategies members of social networking sites used to gain information about a person who they had recently met online. The second aim was to investigate whether and how these uncertainty reduction strategies resulted in social

  2. An Online Social Networking Approach to Reinforce Learning of Rocks and Minerals

    Science.gov (United States)

    Kennelly, Patrick

    2009-01-01

    Numerous and varied methods are used in introductory Earth science and geology classes to help students learn about rocks and minerals, such as classroom lectures, laboratory specimen identification, and field trips. This paper reports on a method using online social networking. The choice of this forum was based on two criteria. First, many…

  3. Literacy and Capital in Immigrant Youths' Online Networks across Countries

    Science.gov (United States)

    Lam, Wan Shun Eva

    2014-01-01

    Communication technologies are playing an increasingly prominent role in facilitating immigrants' social networks across countries and the transnational positioning of immigrant youth in their online language and literacy practices. Drawing from a comparative case study of the digital literacy practices of immigrant youth of Chinese descent,…

  4. The social sharing of emotion (SSE) in online social networks: a case study in Live Journal

    NARCIS (Netherlands)

    Rodriguez Hidalgo, C.T.; Tan, E.S.; Verlegh, P.W.J.

    2015-01-01

    Social Sharing of Emotion (SSE) occurs when one person shares an emotional experience with another and is considered potentially beneficial. Though social sharing has been shown prevalent in interpersonal communication, research on its occurrence and communication structure in online social networks

  5. POSTER: Privacy-Preserving Profile Similarity Computation in Online Social Networks

    NARCIS (Netherlands)

    Jeckmans, Arjan; Tang, Qiang; Hartel, Pieter H.

    2011-01-01

    Currently, none of the existing online social networks (OSNs) enables its users to make new friends without revealing their private information. This leaves the users in a vulnerable position when searching for new friends. We propose a solution which enables a user to compute her profile similarity

  6. Online Learning of Genetic Network Programming and its Application to Prisoner’s Dilemma Game

    Science.gov (United States)

    Mabu, Shingo; Hirasawa, Kotaro; Hu, Jinglu; Murata, Junichi

    A new evolutionary model with the network structure named Genetic Network Programming (GNP) has been proposed recently. GNP, that is, an expansion of GA and GP, represents solutions as a network structure and evolves it by using “offline learning (selection, mutation, crossover)”. GNP can memorize the past action sequences in the network flow, so it can deal with Partially Observable Markov Decision Process (POMDP) well. In this paper, in order to improve the ability of GNP, Q learning (an off-policy TD control algorithm) that is one of the famous online methods is introduced for online learning of GNP. Q learning is suitable for GNP because (1) in reinforcement learning, the rewards an agent will get in the future can be estimated, (2) TD control doesn’t need much memory and can learn quickly, and (3) off-policy is suitable in order to search for an optimal solution independently of the policy. Finally, in the simulations, online learning of GNP is applied to a player for “Prisoner’s dilemma game” and its ability for online adaptation is confirmed.

  7. The Use of Online Social Networks by Polish Former Erasmus Students: A Large-Scale Survey

    Science.gov (United States)

    Bryla, Pawel

    2014-01-01

    There is an increasing role of online social networks in the life of young Poles. We conducted a large-scale survey among Polish former Erasmus students. We have received 2450 completed questionnaires from alumni of 115 higher education institutions all over Poland. 85.4% of our respondents reported they kept in touch with their former Erasmus…

  8. Social Capital, Self-Esteem, and Use of Online Social Network Sites: A Longitudinal Analysis

    Science.gov (United States)

    Steinfield, Charles; Ellison, Nicole B.; Lampe, Cliff

    2008-01-01

    A longitudinal analysis of panel data from users of a popular online social network site, Facebook, investigated the relationship between intensity of Facebook use, measures of psychological well-being, and bridging social capital. Two surveys conducted a year apart at a large U.S. university, complemented with in-depth interviews with 18 Facebook…

  9. An Online Life Like Any Other: Identity, Self-Determination, and Social Networking Among Adults with Intellectual Disabilities.

    Science.gov (United States)

    Chadwick, Darren D; Fullwood, Chris

    2018-01-01

    Research focusing on online identity and the personal experiences of adults with intellectual disabilities (ID) is currently limited. Eleven adults with ID were interviewed regarding personal experiences of being online and using social media. Data were analyzed qualitatively using thematic network analysis. Two global themes, online relatedness and sharing and online agency and support, highlighted the positive potential of social media in enabling the development and maintenance of social bonds, valued social roles, and feelings of enjoyment, competence, autonomy, and self-worth. Participants reported sharing various expressed online identities that did not focus on or hide impairment, challenging notions of dependency, with participants both providing support and being supported online.

  10. Multirelational organization of large-scale social networks in an online world.

    Science.gov (United States)

    Szell, Michael; Lambiotte, Renaud; Thurner, Stefan

    2010-08-03

    The capacity to collect fingerprints of individuals in online media has revolutionized the way researchers explore human society. Social systems can be seen as a nonlinear superposition of a multitude of complex social networks, where nodes represent individuals and links capture a variety of different social relations. Much emphasis has been put on the network topology of social interactions, however, the multidimensional nature of these interactions has largely been ignored, mostly because of lack of data. Here, for the first time, we analyze a complete, multirelational, large social network of a society consisting of the 300,000 odd players of a massive multiplayer online game. We extract networks of six different types of one-to-one interactions between the players. Three of them carry a positive connotation (friendship, communication, trade), three a negative (enmity, armed aggression, punishment). We first analyze these types of networks as separate entities and find that negative interactions differ from positive interactions by their lower reciprocity, weaker clustering, and fatter-tail degree distribution. We then explore how the interdependence of different network types determines the organization of the social system. In particular, we study correlations and overlap between different types of links and demonstrate the tendency of individuals to play different roles in different networks. As a demonstration of the power of the approach, we present the first empirical large-scale verification of the long-standing structural balance theory, by focusing on the specific multiplex network of friendship and enmity relations.

  11. Followers are not enough: a multifaceted approach to community detection in online social networks.

    Science.gov (United States)

    Darmon, David; Omodei, Elisa; Garland, Joshua

    2015-01-01

    In online social media networks, individuals often have hundreds or even thousands of connections, which link these users not only to friends, associates, and colleagues, but also to news outlets, celebrities, and organizations. In these complex social networks, a 'community' as studied in the social network literature, can have very different meaning depending on the property of the network under study. Taking into account the multifaceted nature of these networks, we claim that community detection in online social networks should also be multifaceted in order to capture all of the different and valuable viewpoints of 'community.' In this paper we focus on three types of communities beyond follower-based structural communities: activity-based, topic-based, and interaction-based. We analyze a Twitter dataset using three different weightings of the structural network meant to highlight these three community types, and then infer the communities associated with these weightings. We show that interesting insights can be obtained about the complex community structure present in social networks by studying when and how these four community types give rise to similar as well as completely distinct community structure.

  12. Advanced Networks in Dental Rich Online MEDiA (ANDROMEDA)

    Science.gov (United States)

    Elson, Bruce; Reynolds, Patricia; Amini, Ardavan; Burke, Ezra; Chapman, Craig

    There is growing demand for dental education and training not only in terms of knowledge but also skills. This demand is driven by continuing professional development requirements in the more developed economies, personnel shortages and skills differences across the European Union (EU) accession states and more generally in the developing world. There is an excellent opportunity for the EU to meet this demand by developing an innovative online flexible learning platform (FLP). Current clinical online systems are restricted to the delivery of general, knowledge-based training with no easy method of personalization or delivery of skill-based training. The PHANTOM project, headed by Kings College London is developing haptic-based virtual reality training systems for clinical dental training. ANDROMEDA seeks to build on this and establish a Flexible Learning Platform that can integrate the haptic and sensor based training with rich media knowledge transfer, whilst using sophisticated technologies such as including service-orientated architecture (SOA), Semantic Web technologies, knowledge-based engineering, business intelligence (BI) and virtual worlds for personalization.

  13. Professionalism in Student Online Social Networking: The Role of Educators

    Science.gov (United States)

    Chester, A.; Kienhuis, M.; Pisani, H.; Shahwan-Akl, L.; White, K.

    2013-01-01

    Social media now form a common part of university students' experience. Both at university and after graduation, in their personal and professional lives, social media offer opportunities for connection previously unavailable. The ubiquitous nature of social networking has brought with it professional and ethical issues that need to be…

  14. Bayesian Inference and Online Learning in Poisson Neuronal Networks.

    Science.gov (United States)

    Huang, Yanping; Rao, Rajesh P N

    2016-08-01

    Motivated by the growing evidence for Bayesian computation in the brain, we show how a two-layer recurrent network of Poisson neurons can perform both approximate Bayesian inference and learning for any hidden Markov model. The lower-layer sensory neurons receive noisy measurements of hidden world states. The higher-layer neurons infer a posterior distribution over world states via Bayesian inference from inputs generated by sensory neurons. We demonstrate how such a neuronal network with synaptic plasticity can implement a form of Bayesian inference similar to Monte Carlo methods such as particle filtering. Each spike in a higher-layer neuron represents a sample of a particular hidden world state. The spiking activity across the neural population approximates the posterior distribution over hidden states. In this model, variability in spiking is regarded not as a nuisance but as an integral feature that provides the variability necessary for sampling during inference. We demonstrate how the network can learn the likelihood model, as well as the transition probabilities underlying the dynamics, using a Hebbian learning rule. We present results illustrating the ability of the network to perform inference and learning for arbitrary hidden Markov models.

  15. Engagement with News Content in Online Social Networks

    Science.gov (United States)

    Oeldorf-Hirsch, Anne

    2011-01-01

    Reports indicate that as the Internet is displacing traditional news sources, younger users continue to be disconnected from the news. Fortunately, the Internet provides new ways of sharing and discussing news stories with others through social networking sites such as Facebook, which may be important for engaging users in the news they read…

  16. Uncovering the essential links in online commercial networks

    Science.gov (United States)

    Zeng, Wei; Fang, Meiling; Shao, Junming; Shang, Mingsheng

    2016-09-01

    Recommender systems are designed to effectively support individuals' decision-making process on various web sites. It can be naturally represented by a user-object bipartite network, where a link indicates that a user has collected an object. Recently, research on the information backbone has attracted researchers' interests, which is a sub-network with fewer nodes and links but carrying most of the relevant information. With the backbone, a system can generate satisfactory recommenda- tions while saving much computing resource. In this paper, we propose an enhanced topology-aware method to extract the information backbone in the bipartite network mainly based on the information of neighboring users and objects. Our backbone extraction method enables the recommender systems achieve more than 90% of the accuracy of the top-L recommendation, however, consuming only 20% links. The experimental results show that our method outperforms the alternative backbone extraction methods. Moreover, the structure of the information backbone is studied in detail. Finally, we highlight that the information backbone is one of the most important properties of the bipartite network, with which one can significantly improve the efficiency of the recommender system.

  17. Informal Learning and Identity Formation in Online Social Networks

    Science.gov (United States)

    Greenhow, Christine; Robelia, Beth

    2009-01-01

    All students today are increasingly expected to develop technological fluency, digital citizenship, and other twenty-first century competencies despite wide variability in the quality of learning opportunities schools provide. Social network sites (SNSs) available via the internet may provide promising contexts for learning to supplement…

  18. Online Social Networks and Computer Skills of University Students

    Science.gov (United States)

    Barbas, Maria Potes; Valerio, Gabriel; Rodríguez-Martínez, María del Carmen; Herrera-Murillo, Dagoberto José; Belmonte-Jiménez, Ana María

    2014-01-01

    Currently a large number of college students belong to social networks and spend several hours a week on them. Some sectors of society, like parents and teachers, are concerned about the negative impact on their academic work and in their personal lives. However, because the potential positive impacts have not been explored enough, this research…

  19. Growing up with Social Networks and Online Communities

    Science.gov (United States)

    Strom, Paris; Strom, Robert

    2012-01-01

    This presentation examines child and adolescent social networking with an emphasis on how this unprecedented form of communication can be used to contribute to healthy growth and development. Most literature about child and adolescent relationships reflects yesterday's world, a time when face-to-face encounters were the only concern. Students saw…

  20. Dynamics of user networks in on-line electronic auctions

    Czech Academy of Sciences Publication Activity Database

    Slanina, František

    2014-01-01

    Roč. 17, č. 1 (2014), "1450002-1"-"1450002-14" ISSN 0219-5259 R&D Projects: GA MŠk OC09078 Institutional support: RVO:68378271 Keywords : networks * random graphs * dynamics Subject RIV: BE - Theoretical Physics Impact factor: 0.968, year: 2014

  1. On-line validation of feedwater flow rate in nuclear power plants using neural networks

    International Nuclear Information System (INIS)

    Khadem, M.; Ipakchi, A.; Alexandro, F.J.; Colley, R.W.

    1994-01-01

    On-line calibration of feedwater flow rate measurement in nuclear power plants provides a continuous realistic value of feedwater flow rate. It also reduces the manpower required for periodic calibration needed due to the fouling and defouling of the venturi meter surface condition. This paper presents a method for on-line validation of feedwater flow rate in nuclear power plants. The method is an improvement of the previously developed method which is based on the use of a set of process variables dynamically related to the feedwater flow rate. The online measurements of this set of variables are used as inputs to a neural network to obtain an estimate of the feedwater flow rate reading. The difference between the on-line feedwater flow rate reading, and the neural network estimate establishes whether there is a need to apply a correction factor to the feedwater flow rate measurement for calculation of the actual reactor power. The method was applied to the feedwater flow meters in the two feedwater flow loops of the TMI-1 nuclear power plant. The venturi meters used for flow measurements are susceptible to frequent fouling that degrades their measurement accuracy. The fouling effects can cause an inaccuracy of up to 3% relative error in feedwater flow rate reading. A neural network, whose inputs were the readings of a set of reference instruments, was designed to predict both feedwater flow rates simultaneously. A multi-layer feedforward neural network employing the backpropagation algorithm was used. A number of neural network training tests were performed to obtain an optimum filtering technique of the input/output data of the neural networks. The result of the selection of the filtering technique was confirmed by numerous Fast Fourier Transform (FFT) tests. Training and testing were done on data from TMI-1 nuclear power plant. The results show that the neural network can predict the correct flow rates with an absolute relative error of less than 2%

  2. Network Biology (http://www.iaees.org/publications/journals/nb/online-version.asp

    Directory of Open Access Journals (Sweden)

    networkbiology@iaees.org

    Full Text Available Network Biology ISSN 2220-8879 URL: http://www.iaees.org/publications/journals/nb/online-version.asp RSS: http://www.iaees.org/publications/journals/nb/rss.xml E-mail: networkbiology@iaees.org Editor-in-Chief: WenJun Zhang Aims and Scope NETWORK BIOLOGY (ISSN 2220-8879; CODEN NBEICS is an open access, peer-reviewed international journal that considers scientific articles in all different areas of network biology. It is the transactions of the International Society of Network Biology. It dedicates to the latest advances in network biology. The goal of this journal is to keep a record of the state-of-the-art research and promote the research work in these fast moving areas. The topics to be covered by Network Biology include, but are not limited to: •Theories, algorithms and programs of network analysis •Innovations and applications of biological networks •Ecological networks, food webs and natural equilibrium •Co-evolution, co-extinction, biodiversity conservation •Metabolic networks, protein-protein interaction networks, biochemical reaction networks, gene networks, transcriptional regulatory networks, cell cycle networks, phylogenetic networks, network motifs •Physiological networksNetwork regulation of metabolic processes, human diseases and ecological systems •Social networks, epidemiological networks •System complexity, self-organized systems, emergence of biological systems, agent-based modeling, individual-based modeling, neural network modeling, and other network-based modeling, etc. We are also interested in short communications that clearly address a specific issue or completely present a new ecological network, food web, or metabolic or gene network, etc. Authors can submit their works to the email box of this journal, networkbiology@iaees.org. All manuscripts submitted to this journal must be previously unpublished and may not be considered for publication elsewhere at any time during review period of this journal

  3. Peer influences: the impact of online and offline friendship networks on adolescent smoking and alcohol use.

    Science.gov (United States)

    Huang, Grace C; Unger, Jennifer B; Soto, Daniel; Fujimoto, Kayo; Pentz, Mary Ann; Jordan-Marsh, Maryalice; Valente, Thomas W

    2014-05-01

    Online social networking sites (SNSs) have become a popular mode of communication among adolescents. However, little is known about the effects of social online activity on health behaviors. The authors examined the use of SNSs among friends and the degree to which SNS activities relate to face-to-face peer influences and adolescent risk behaviors. Longitudinal egocentric friendship network data along with adolescent social media use and risk behaviors were collected from 1,563 10th-grade students across five Southern California high schools. Measures of online and offline peer influences were computed and assessed using fixed-effects models. The frequency of adolescent SNS use and the number of their closest friends on the same SNSs were not significantly associated with risk behaviors. However, exposure to friends' online pictures of partying or drinking was significantly associated with both smoking (β = .11, p < .001) and alcohol use (β = .06, p < .05). Whereas adolescents with drinking friends had higher risk levels for drinking, adolescents without drinking friends were more likely to be affected by higher exposure to risky online pictures (β = -.10, p < .05). Myspace and Facebook had demographically distinct user characteristics and differential effects on risk behaviors. Exposure to risky online content had a direct impact on adolescents' risk behaviors and significantly interacted with risk behaviors of their friends. These results provide evidence that friends' online behaviors should be considered a viable source of peer influence and that increased efforts should focus on educating adolescents on the negative effects of risky online displays. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  4. The Relationship Between Use of Social Network Sites, Online Social Support, and Well-Being

    Science.gov (United States)

    2017-01-01

    Abstract. Existing work on the effects of social network sites (SNS) on well-being has often stressed that SNS can help people gain social support from their online networks, which positively affects their well-being. However, the majority of studies in this area have been cross-sectional in nature and/or relied on student samples. Using data from six waves of a longitudinal study with a representative sample of Dutch Internet users, we first examined whether users and nonusers of SNS differ in online social support and well-being (as indicated by life satisfaction and stress). In a second step, we investigated in more detail how SNS use – more specifically, asking for advice and the number of strong ties on these SNS – are related to online social support, stress, and satisfaction with life. Overall, our results provide no evidence for SNS use and online social support affecting either stress or life satisfaction. SNS users reported more online social support than nonusers did, but also higher levels of stress; the two groups did not differ in overall life satisfaction. With regard to the underlying processes, we found positive cross-sectional and longitudinal relationships between asking for advice on SNS and online social support, indicating that SNS can be an effective tool for receiving social support. However, online social support was not related to higher life satisfaction or reduced stress 6 months later; instead, it seems that SNS users with lower life satisfaction and/or higher stress seek more social support online by asking for advice on SNS. PMID:29147141

  5. Engineering Online and In-person Social Networks for Physical Activity: A Randomized Trial

    Science.gov (United States)

    Rovniak, Liza S.; Kong, Lan; Hovell, Melbourne F.; Ding, Ding; Sallis, James F.; Ray, Chester A.; Kraschnewski, Jennifer L.; Matthews, Stephen A.; Kiser, Elizabeth; Chinchilli, Vernon M.; George, Daniel R.; Sciamanna, Christopher N.

    2016-01-01

    Background Social networks can influence physical activity, but little is known about how best to engineer online and in-person social networks to increase activity. Purpose To conduct a randomized trial based on the Social Networks for Activity Promotion model to assess the incremental contributions of different procedures for building social networks on objectively-measured outcomes. Methods Physically inactive adults (n = 308, age, 50.3 (SD = 8.3) years, 38.3% male, 83.4% overweight/obese) were randomized to 1 of 3 groups. The Promotion group evaluated the effects of weekly emailed tips emphasizing social network interactions for walking (e.g., encouragement, informational support); the Activity group evaluated the incremental effect of adding an evidence-based online fitness walking intervention to the weekly tips; and the Social Networks group evaluated the additional incremental effect of providing access to an online networking site for walking, and prompting walking/activity across diverse settings. The primary outcome was mean change in accelerometer-measured moderate-to-vigorous physical activity (MVPA), assessed at 3 and 9 months from baseline. Results Participants increased their MVPA by 21.0 mins/week, 95% CI [5.9, 36.1], p = .005, at 3 months, and this change was sustained at 9 months, with no between-group differences. Conclusions Although the structure of procedures for targeting social networks varied across intervention groups, the functional effect of these procedures on physical activity was similar. Future research should evaluate if more powerful reinforcers improve the effects of social network interventions. Trial Registration Number NCT01142804 PMID:27405724

  6. Engineering Online and In-Person Social Networks for Physical Activity: A Randomized Trial.

    Science.gov (United States)

    Rovniak, Liza S; Kong, Lan; Hovell, Melbourne F; Ding, Ding; Sallis, James F; Ray, Chester A; Kraschnewski, Jennifer L; Matthews, Stephen A; Kiser, Elizabeth; Chinchilli, Vernon M; George, Daniel R; Sciamanna, Christopher N

    2016-12-01

    Social networks can influence physical activity, but little is known about how best to engineer online and in-person social networks to increase activity. The purpose of this study was to conduct a randomized trial based on the Social Networks for Activity Promotion model to assess the incremental contributions of different procedures for building social networks on objectively measured outcomes. Physically inactive adults (n = 308, age, 50.3 (SD = 8.3) years, 38.3 % male, 83.4 % overweight/obese) were randomized to one of three groups. The Promotion group evaluated the effects of weekly emailed tips emphasizing social network interactions for walking (e.g., encouragement, informational support); the Activity group evaluated the incremental effect of adding an evidence-based online fitness walking intervention to the weekly tips; and the Social Networks group evaluated the additional incremental effect of providing access to an online networking site for walking as well as prompting walking/activity across diverse settings. The primary outcome was mean change in accelerometer-measured moderate-to-vigorous physical activity (MVPA), assessed at 3 and 9 months from baseline. Participants increased their MVPA by 21.0 min/week, 95 % CI [5.9, 36.1], p = .005, at 3 months, and this change was sustained at 9 months, with no between-group differences. Although the structure of procedures for targeting social networks varied across intervention groups, the functional effect of these procedures on physical activity was similar. Future research should evaluate if more powerful reinforcers improve the effects of social network interventions. The trial was registered with the ClinicalTrials.gov (NCT01142804).

  7. Diffusion of influence in energy awareness campaigns on the online social networking site of facebook

    Energy Technology Data Exchange (ETDEWEB)

    Samaha, Kimberly

    2010-09-15

    The era of government jurisdiction based on separate and autonomous entities has been replaced with an intergovernmental and intersectoral network of industry, regulators, special interest groups and individual citizens. New forms of regulatory feedback will be inspired more by the concepts of networks- they will be flatter, leaner, and more flexible. An evaluation of new methods for the diffusion of public awareness regarding energy technologies, policies and projects, was conducted using the technology platform of Facebook. This paper reports on the results of an eighteen month formal study of the Diffusion of Influence in Online Social Networks.

  8. School Absenteeism: An Online Survey via Social Networks.

    Science.gov (United States)

    Pflug, Verena; Schneider, Silvia

    2016-06-01

    School absenteeism is a significant social and public health problem. However, existing prevalence rates are often not representative due to biased assessment processes at schools. The present study assessed school absenteeism in Germany using a nationwide online self-report survey. Although our definition of school absenteeism was more conservative than in previous studies, nearly 9 % of the 1359 high school students reported school absenteeism within the past 7 days. Absent students lived less often with both parents, were on average of lower socioeconomic status, and reported more emotional problems, behavioral problems and less prosocial behavior than attending students. Being an indicator of a wide variety of problems in children and adolescents, school absenteeism deserves much more attention. Future directions for research and implications for prevention and intervention programs are discussed.

  9. Exploring mobile health in a private online social network.

    Science.gov (United States)

    Memon, Qurban A; Mustafa, Asma Fayes

    2015-01-01

    Health information is very vulnerable. Certain individuals or corporate organisations will continue to steal it similar to bank account data once data is on wireless channels. Once health information is part of a social network, corresponding privacy issues also surface. Insufficiently trained employees at hospitals that pay less attention to creating a privacy-aware culture will suffer loss when mobile devices containing health information are lost, stolen or sniffed. In this work, a social network system is explored as a m-health system from a privacy perspective. A model is developed within a framework of data-driven privacy and implemented on Android operating system. In order to check feasibility of the proposed model, a prototype application is developed on Facebook for different services, including: i) sharing user location; ii) showing nearby friends; iii) calculating and sharing distance moved, and calories burned; iv) calculating, tracking and sharing user heart rate; etc.

  10. MATLAB Simulation of Gradient-Based Neural Network for Online Matrix Inversion

    Science.gov (United States)

    Zhang, Yunong; Chen, Ke; Ma, Weimu; Li, Xiao-Dong

    This paper investigates the simulation of a gradient-based recurrent neural network for online solution of the matrix-inverse problem. Several important techniques are employed as follows to simulate such a neural system. 1) Kronecker product of matrices is introduced to transform a matrix-differential-equation (MDE) to a vector-differential-equation (VDE); i.e., finally, a standard ordinary-differential-equation (ODE) is obtained. 2) MATLAB routine "ode45" is introduced to solve the transformed initial-value ODE problem. 3) In addition to various implementation errors, different kinds of activation functions are simulated to show the characteristics of such a neural network. Simulation results substantiate the theoretical analysis and efficacy of the gradient-based neural network for online constant matrix inversion.

  11. Exploring Co-studied Massive Open Online Course Subjects via Social Network Analysis

    Directory of Open Access Journals (Sweden)

    Katy Jordan

    2014-06-01

    Full Text Available Massive Open Online Courses (MOOCs allow students to study online courses without requiring previous experience or qualifications. This offers students the freedom to study a wide variety of topics, freed from the curriculum of a degree programme for example; however, it also poses a challenge for students in terms of making connections between individual courses. This paper examines the subjects which students at one MOOC platform (Coursera choose to study. It uses a social network analysis based approach to create a network graph of co-studied subjects. The resulting network demonstrates a good deal of overlap between different disciplinary areas. Communities are identified within the graph and characterised. The results suggests that MOOC students may not be seeking to replicate degree-style courses in one specialist area, which may have implications for the future moves toward ‘MOOCs for credit’.

  12. Online social networks that connect users to physical activity partners: a review and descriptive analysis.

    Science.gov (United States)

    Nakhasi, Atul; Shen, Album Xiaotian; Passarella, Ralph Joseph; Appel, Lawrence J; Anderson, Cheryl Am

    2014-06-16

    The US Centers for Disease Control and Prevention have identified a lack of encouragement, support, or companionship from family and friends as a major barrier to physical activity. To overcome this barrier, online social networks are now actively leveraging principles of companion social support in novel ways. The aim was to evaluate the functionality, features, and usability of existing online social networks which seek to increase physical activity and fitness among users by connecting them to physical activity partners, not just online, but also face-to-face. In September 2012, we used 3 major databases to identify the website addresses for relevant online social networks. We conducted a Google search using 8 unique keyword combinations: the common keyword "find" coupled with 1 of 4 prefix terms "health," "fitness," "workout," or "physical" coupled with 1 of 2 stem terms "activity partners" or "activity buddies." We also searched 2 prominent technology start-up news sites, TechCrunch and Y Combinator, using 2 unique keyword combinations: the common keyword "find" coupled with 1 of 2 stem terms "activity partners" and "activity buddies." Sites were defined as online social health activity networks if they had the ability to (1) actively find physical activity partners or activities for the user, (2) offer dynamic, real-time tracking or sharing of social activities, and (3) provide virtual profiles to users. We excluded from our analysis sites that were not Web-based, publicly available, in English, or free. Of the 360 initial search results, we identified 13 websites that met our complete criteria of an online social health activity network. Features such as physical activity creation (13/13, 100%) and private messaging (12/13, 92%) appeared almost universally among these websites. However, integration with Web 2.0 technologies such as Facebook and Twitter (9/13, 69%) and the option of direct event joining (8/13, 62%) were not as universally present. Largely

  13. The spreading of opposite opinions on online social networks with authoritative nodes

    Science.gov (United States)

    Yan, Shu; Tang, Shaoting; Pei, Sen; Jiang, Shijin; Zhang, Xiao; Ding, Wenrui; Zheng, Zhiming

    2013-09-01

    The study of opinion dynamics, such as spreading and controlling of rumors, has become an important issue on social networks. Numerous models have been devised to describe this process, including epidemic models and spin models, which mainly focus on how opinions spread and interact with each other, respectively. In this paper, we propose a model that combines the spreading stage and the interaction stage for opinions to illustrate the process of dispelling a rumor. Moreover, we set up authoritative nodes, which disseminate positive opinion to counterbalance the negative opinion prevailing on online social networking sites. With analysis of the relationship among positive opinion proportion, opinion strength and the density of authoritative nodes in networks with different topologies, we demonstrate that the positive opinion proportion grows with the density of authoritative nodes until the positive opinion prevails in the entire network. In particular, the relationship is linear in homogeneous topologies. Besides, it is also noteworthy that initial locations of the negative opinion source and authoritative nodes do not influence positive opinion proportion in homogeneous networks but have a significant impact on heterogeneous networks. The results are verified by numerical simulations and are helpful to understand the mechanism of two different opinions interacting with each other on online social networking sites.

  14. Offline constraints in online drug marketplaces: An exploratory analysis of a cryptomarket trade network.

    Science.gov (United States)

    Norbutas, Lukas

    2018-06-01

    Cryptomarkets, or illegal anonymizing online platforms that facilitate drug trade, have been analyzed in a rapidly growing body of research. Previous research has found that, despite increased risks, cryptomarket sellers are often willing to ship illegal drugs internationally. There is little to no information, however, about the extent to which uncertainty and risk related to geographic constraints shapes buyers' behavior and, in turn, the structure of the global online drug trade network. In this paper, we analyze the structure of a complete cryptomarket trade network with a focus on the role of geographic clustering of buyers and sellers. We use publicly available crawls of the cryptomarket Abraxas, encompassing market transactions between 463 sellers and 3542 buyers of drugs in 2015. We use descriptive social network analysis and Exponential Random Graph Models (ERGM) to analyze the structure of the trade network. The structure of the online drug trade network is primarily shaped by geographical boundaries. Buyers are more likely to buy from multiple sellers within a single country, and avoid buying from sellers in different countries, which leads to strong geographic clustering. The effect is especially strong between continents and weaker for countries within Europe. A small fraction of buyers (10%) account for more than a half of all drug purchases, while most buyers only buy once. Online drug trade networks might still be heavily shaped by offline (geographic) constraints, despite their ability to provide access for end-users to large international supply. Cryptomarkets might be more "localized" and less international than thought before. We discuss potential explanations for such geographical clustering and implications of the findings. Copyright © 2018 The Author(s). Published by Elsevier B.V. All rights reserved.

  15. Professional conduct among registered nurses in the use of online social networking sites.

    Science.gov (United States)

    Levati, Sara

    2014-10-01

    To explore the use of Facebook by Registered Nurses (RNs) in Italy and the United Kingdom (UK), focusing on the disclosure of personal and professional information. The use of online social network sites among medical students and doctors is posing new ethical challenges to the profession. To date, little research has explored the use of online social networking sites among nurses. A cross-national survey. Data were assessed on 124 nurses' profile pages, readily available without viewing restrictions. Content analysis and inferential statistics were undertaken to describe usage and identify similarities and differences between the two country-groups of nurses. Data were collected between December 2011-January 2012. Overall, UK and Italian RNs showed a similar use of the online platform, tending to disclose personal pictures, home town and current home location, as well as updates and comments related to personal and work-related activities. A statistically significant higher proportion of nurses in Italy disclosed their sexual orientation. In both groups, a few cases were observed of potentially unprofessional content in relation to the use of alcohol, nudity and material of a salacious nature. Although most of the UK and Italy RNs appear to be aware of the risks posed by their online exposure, their online activity indicates the blurring of their personal and professional lives; this is posing new ethical, legal and professional challenges to members of the nursing profession. Further research and debate is encouraged at national and international level. © 2014 John Wiley & Sons Ltd.

  16. The Method of Building a Network of Online Showcases on the Basis of the MVC Architecture

    Directory of Open Access Journals (Sweden)

    Pursky Oleg I.

    2017-10-01

    Full Text Available A method to build a network of online showcases that support a large number of customer orders and visits, which meets the current performance standards and the reliability of Internet solutions in the sphere electronic commerce, has been developed. The method involves the creation of a typical showcase and the implementation for the information management system of a showcases network of an own database operating on the data from the central management information system with the two-way data replication. A mechanism for «cloning» the online showcases, which are part of the network, and their quick integration with the business processes of enterprise and a management system based on a typical showcase, has been proposed. The development of typical online showcases is implemented on the basis of MVC concept (Model-View-Controller, the ASP.NET MVC Framework Technology, and the visual templates of web pages, thus ensuring that the algorithms for the behavior of objects are independent of both the objects themselves and their visual representation. This enhances the development of e-commerce projects significantly, speeds up the implementation process, and provides a high degree of flexibility and functionality of the online showcases.

  17. Online Self-Organizing Network Control with Time Averaged Weighted Throughput Objective

    Directory of Open Access Journals (Sweden)

    Zhicong Zhang

    2018-01-01

    Full Text Available We study an online multisource multisink queueing network control problem characterized with self-organizing network structure and self-organizing job routing. We decompose the self-organizing queueing network control problem into a series of interrelated Markov Decision Processes and construct a control decision model for them based on the coupled reinforcement learning (RL architecture. To maximize the mean time averaged weighted throughput of the jobs through the network, we propose a reinforcement learning algorithm with time averaged reward to deal with the control decision model and obtain a control policy integrating the jobs routing selection strategy and the jobs sequencing strategy. Computational experiments verify the learning ability and the effectiveness of the proposed reinforcement learning algorithm applied in the investigated self-organizing network control problem.

  18. Management, Optimization and Evolution of the LHCb Online Network

    CERN Document Server

    Liu, G; Savriè, M; Neufeld, N

    2010-01-01

    The LHCb experiment is one of the four large particle detectors operated at the Large Hadron Collider (LHC) at CERN. It is a forward single-arm spectrometer dedicated to test the Standard Model through precision measurements of Charge-Parity (CP) violation and rare decays in the b quark sector. The LHCb experiment will operate at a luminosity of 2 x 10$^{32}cm^{-2}s^{-1}$, the proton-proton bunch crossings rate will be approximately 10 MHz. To select the interesting events, a two-level trigger scheme is applied: the first level trigger (L0) and the high level trigger (HLT). The L0 trigger is implemented in custom hardware, while HLT is implemented in software running on the CPUs of the Event Filter Farm (EFF). The L0 trigger rate is limited to about 1 MHz, and the event size for each event is about 35 kByte. It is a big challenge to handle the resulting data rate (35GByte/s). The online system is a key part of the LHCb experiment, providing all the IT services. It consists of three major components: the Data ...

  19. Understanding the Context of Learning in an Online Social Network for Health Professionals' Informal Learning.

    Science.gov (United States)

    Li, Xin; Gray, Kathleen; Verspoor, Karin; Barnett, Stephen

    2017-01-01

    Online social networks (OSN) enable health professionals to learn informally, for example by sharing medical knowledge, or discussing practice management challenges and clinical issues. Understanding the learning context in OSN is necessary to get a complete picture of the learning process, in order to better support this type of learning. This study proposes critical contextual factors for understanding the learning context in OSN for health professionals, and demonstrates how these contextual factors can be used to analyse the learning context in a designated online learning environment for health professionals.

  20. Predicting ethnicity with first names in online social media networks

    Directory of Open Access Journals (Sweden)

    Bas Hofstra

    2018-03-01

    Full Text Available Social scientists increasingly use (big social media data to illuminate long-standing substantive questions in social science research. However, a key challenge of analyzing such data is their lower level of individual detail compared to highly detailed survey data. This limits the scope of substantive questions that can be addressed with these data. In this study, we provide a method to upgrade individual detail in terms of ethnicity in data gathered from social media via the use of register data. Our research aim is twofold: first, we predict the most likely value of ethnicity, given one's first name, and second, we show how one can test hypotheses with the predicted values for ethnicity as an independent variable while simultaneously accounting for the uncertainty in these predictions. We apply our method to social network data collected from Facebook. We illustrate our approach and provide an example of hypothesis testing using our procedure, i.e., estimating the relation between predicted network ethnic homogeneity on Facebook and trust in institutions. In a comparison of our method with two other methods, we find that our method provides the most conservative tests of hypotheses. We discuss the promise of our approach and pinpoint future research directions.

  1. Are health behavior change interventions that use online social networks effective? A systematic review.

    Science.gov (United States)

    Maher, Carol A; Lewis, Lucy K; Ferrar, Katia; Marshall, Simon; De Bourdeaudhuij, Ilse; Vandelanotte, Corneel

    2014-02-14

    The dramatic growth of Web 2.0 technologies and online social networks offers immense potential for the delivery of health behavior change campaigns. However, it is currently unclear how online social networks may best be harnessed to achieve health behavior change. The intent of the study was to systematically review the current level of evidence regarding the effectiveness of online social network health behavior interventions. Eight databases (Scopus, CINAHL, Medline, ProQuest, EMBASE, PsycINFO, Cochrane, Web of Science and Communication & Mass Media Complete) were searched from 2000 to present using a comprehensive search strategy. Study eligibility criteria were based on the PICOS format, where "population" included child or adult populations, including healthy and disease populations; "intervention" involved behavior change interventions targeting key modifiable health behaviors (tobacco and alcohol consumption, dietary intake, physical activity, and sedentary behavior) delivered either wholly or in part using online social networks; "comparator" was either a control group or within subject in the case of pre-post study designs; "outcomes" included health behavior change and closely related variables (such as theorized mediators of health behavior change, eg, self-efficacy); and "study design" included experimental studies reported in full-length peer-reviewed sources. Reports of intervention effectiveness were summarized and effect sizes (Cohen's d and 95% confidence intervals) were calculated wherever possible. Attrition (percentage of people who completed the study), engagement (actual usage), and fidelity (actual usage/intended usage) with the social networking component of the interventions were scrutinized. A total of 2040 studies were identified from the database searches following removal of duplicates, of which 10 met inclusion criteria. The studies involved a total of 113,988 participants (ranging from n=10 to n=107,907). Interventions included

  2. Theoretical approaches of online social network interventions and implications for behavioral change: a systematic review.

    Science.gov (United States)

    Arguel, Amaël; Perez-Concha, Oscar; Li, Simon Y W; Lau, Annie Y S

    2018-02-01

    The aim of this review was to identify general theoretical frameworks used in online social network interventions for behavioral change. To address this research question, a PRISMA-compliant systematic review was conducted. A systematic review (PROSPERO registration number CRD42014007555) was conducted using 3 electronic databases (PsycINFO, Pubmed, and Embase). Four reviewers screened 1788 abstracts. 15 studies were selected according to the eligibility criteria. Randomized controlled trials and controlled studies were assessed using Cochrane Collaboration's "risk-of-bias" tool, and narrative synthesis. Five eligible articles used the social cognitive theory as a framework to develop interventions targeting behavioral change. Other theoretical frameworks were related to the dynamics of social networks, intention models, and community engagement theories. Only one of the studies selected in the review mentioned a well-known theory from the field of health psychology. Conclusions were that guidelines are lacking in the design of online social network interventions for behavioral change. Existing theories and models from health psychology that are traditionally used for in situ behavioral change should be considered when designing online social network interventions in a health care setting. © 2016 John Wiley & Sons, Ltd.

  3. Can online networks provide quality answers to questions about occupational safety and health?

    Science.gov (United States)

    Rhebergen, Martijn D F; Lenderink, Annet F; van Dijk, Frank J H; Hulshof, Carel T J

    2012-05-01

    To assess whether experts can provide high-quality answers to occupational safety and health (OSH) questions in online Question & Answer (Q&A) networks. The authors evaluated the quality of answers provided by qualified experts in two Dutch online networks: ArboAntwoord and the Helpdesk of the Netherlands Center for Occupational Diseases. A random sample of 594 answers was independently evaluated by two raters using nine answer quality criteria. An additional criterion, the agreement of answers with the best available evidence, was explored by peer review of a sample of 42 answers. Reviewers performed an evidence search in Medline. The median answer quality score of ArboAntwoord (N=295) and the Netherlands Center for Occupational Diseases Helpdesk (N=299) was 8 of 9 (IQR 2). The inter-rater reliability of the first nine quality criteria was high (κ 0.82-0.90, p<0.05). A question answered by two or more experts had a greater probability of a high-quality score than questions answered by one expert (OR 4.9, 95% CI 2.7 to 9.0). Answers most often scored insufficient on the use of evidence to underpin the answer (36% and 38% for the networks, respectively) and on conciseness (35% and 31%, respectively). Peer review demonstrated that 43%-72% of the answers in both online networks were in complete agreement with the best available evidence. OSH experts are able to provide quality answers in online OSH Q&A networks. Our answer quality appraisal instrument was feasible and provided information on how to improve answer quality.

  4. EXPLORING THE RELATIONSHIPS AMONG SOCIAL BENEFITS, ONLINE SOCIAL NETWORK DEPENDENCY, SATISFACTION, AND YOUTH’S HABIT FORMATION

    Directory of Open Access Journals (Sweden)

    Tran Van Dat

    2015-12-01

    Full Text Available Online social network is one of the biggest Internet phenomenon, which has attracted the interest of many marketers and psychologists who wanted to understand social network users’ behavior. Recognizing the lack of theoretical and empirical attention that has been given to this field, especially in Vietnam market, this study was conducted to examine the relationships among social benefits, online social network dependency, satisfaction, and youth’s habit formation in the context of Facebook. The findings of the study of 200 Facebook users indicated that the interrelationship among four factors of social benefits, online social network dependency, satisfaction, and habit formation affect each other. Indeed, dependency on online social network among the youth whose age ranged from 16 to 24 years old is significantly affected by social benefits factor and leads to the formation of habit. In addition, satisfaction plays a role in determining habitual Facebook use. This paper discusses theoretical and practical implication in marketing and psychology field.

  5. Modeling the cooperative and competitive contagions in online social networks

    Science.gov (United States)

    Zhuang, Yun-Bei; Chen, J. J.; Li, Zhi-hong

    2017-10-01

    The wide adoption of social media has increased the interaction among different pieces of information, and this interaction includes cooperation and competition for our finite attention. While previous research focus on fully competition, this paper extends the interaction to be both "cooperation" and "competition", by employing an IS1S2 R model. To explore how two different pieces of information interact with each other, the IS1S2 R model splits the agents into four parts-(Ignorant-Spreader I-Spreader II-Stifler), based on SIR epidemic spreading model. Using real data from Weibo.com, a social network site similar to Twitter, we find some parameters, like decaying rates, can both influence the cooperative diffusion process and the competitive process, while other parameters, like infectious rates only have influence on the competitive diffusion process. Besides, the parameters' effect are more significant in the competitive diffusion than in the cooperative diffusion.

  6. Digital divide 2.0: the role of social networking sites in seeking health information online from a longitudinal perspective.

    Science.gov (United States)

    Feng, Yang; Xie, Wenjing

    2015-01-01

    Adopting a longitudinal angle, this study analyzed data from the Pew Internet's Health Tracking Survey in 2006, 2008, and 2010 to identify potential communication inequalities in social networking site use. Results showed that with the growing role of social networking site use in predicting people's likelihood of seeking health information online, the socioeconomic and demographic factors that contributed to the disparities in social networking site use could also lead to disparities in seeking health information online. Also, results indicated that people are more likely to seek heath-related information online if they or their close family or friends have a chronic disease situation.

  7. Methods for Inferring Health-Related Social Networks among Coworkers from Online Communication Patterns

    Science.gov (United States)

    Matthews, Luke J.; DeWan, Peter; Rula, Elizabeth Y.

    2013-01-01

    Studies of social networks, mapped using self-reported contacts, have demonstrated the strong influence of social connections on the propensity for individuals to adopt or maintain healthy behaviors and on their likelihood to adopt health risks such as obesity. Social network analysis may prove useful for businesses and organizations that wish to improve the health of their populations by identifying key network positions. Health traits have been shown to correlate across friendship ties, but evaluating network effects in large coworker populations presents the challenge of obtaining sufficiently comprehensive network data. The purpose of this study was to evaluate methods for using online communication data to generate comprehensive network maps that reproduce the health-associated properties of an offline social network. In this study, we examined three techniques for inferring social relationships from email traffic data in an employee population using thresholds based on: (1) the absolute number of emails exchanged, (2) logistic regression probability of an offline relationship, and (3) the highest ranked email exchange partners. As a model of the offline social network in the same population, a network map was created using social ties reported in a survey instrument. The email networks were evaluated based on the proportion of survey ties captured, comparisons of common network metrics, and autocorrelation of body mass index (BMI) across social ties. Results demonstrated that logistic regression predicted the greatest proportion of offline social ties, thresholding on number of emails exchanged produced the best match to offline network metrics, and ranked email partners demonstrated the strongest autocorrelation of BMI. Since each method had unique strengths, researchers should choose a method based on the aspects of offline behavior of interest. Ranked email partners may be particularly useful for purposes related to health traits in a social network. PMID

  8. Methods for inferring health-related social networks among coworkers from online communication patterns.

    Science.gov (United States)

    Matthews, Luke J; DeWan, Peter; Rula, Elizabeth Y

    2013-01-01

    Studies of social networks, mapped using self-reported contacts, have demonstrated the strong influence of social connections on the propensity for individuals to adopt or maintain healthy behaviors and on their likelihood to adopt health risks such as obesity. Social network analysis may prove useful for businesses and organizations that wish to improve the health of their populations by identifying key network positions. Health traits have been shown to correlate across friendship ties, but evaluating network effects in large coworker populations presents the challenge of obtaining sufficiently comprehensive network data. The purpose of this study was to evaluate methods for using online communication data to generate comprehensive network maps that reproduce the health-associated properties of an offline social network. In this study, we examined three techniques for inferring social relationships from email traffic data in an employee population using thresholds based on: (1) the absolute number of emails exchanged, (2) logistic regression probability of an offline relationship, and (3) the highest ranked email exchange partners. As a model of the offline social network in the same population, a network map was created using social ties reported in a survey instrument. The email networks were evaluated based on the proportion of survey ties captured, comparisons of common network metrics, and autocorrelation of body mass index (BMI) across social ties. Results demonstrated that logistic regression predicted the greatest proportion of offline social ties, thresholding on number of emails exchanged produced the best match to offline network metrics, and ranked email partners demonstrated the strongest autocorrelation of BMI. Since each method had unique strengths, researchers should choose a method based on the aspects of offline behavior of interest. Ranked email partners may be particularly useful for purposes related to health traits in a social network.

  9. Methods for inferring health-related social networks among coworkers from online communication patterns.

    Directory of Open Access Journals (Sweden)

    Luke J Matthews

    Full Text Available Studies of social networks, mapped using self-reported contacts, have demonstrated the strong influence of social connections on the propensity for individuals to adopt or maintain healthy behaviors and on their likelihood to adopt health risks such as obesity. Social network analysis may prove useful for businesses and organizations that wish to improve the health of their populations by identifying key network positions. Health traits have been shown to correlate across friendship ties, but evaluating network effects in large coworker populations presents the challenge of obtaining sufficiently comprehensive network data. The purpose of this study was to evaluate methods for using online communication data to generate comprehensive network maps that reproduce the health-associated properties of an offline social network. In this study, we examined three techniques for inferring social relationships from email traffic data in an employee population using thresholds based on: (1 the absolute number of emails exchanged, (2 logistic regression probability of an offline relationship, and (3 the highest ranked email exchange partners. As a model of the offline social network in the same population, a network map was created using social ties reported in a survey instrument. The email networks were evaluated based on the proportion of survey ties captured, comparisons of common network metrics, and autocorrelation of body mass index (BMI across social ties. Results demonstrated that logistic regression predicted the greatest proportion of offline social ties, thresholding on number of emails exchanged produced the best match to offline network metrics, and ranked email partners demonstrated the strongest autocorrelation of BMI. Since each method had unique strengths, researchers should choose a method based on the aspects of offline behavior of interest. Ranked email partners may be particularly useful for purposes related to health traits in a

  10. Online Distributed Learning Over Networks in RKH Spaces Using Random Fourier Features

    Science.gov (United States)

    Bouboulis, Pantelis; Chouvardas, Symeon; Theodoridis, Sergios

    2018-04-01

    We present a novel diffusion scheme for online kernel-based learning over networks. So far, a major drawback of any online learning algorithm, operating in a reproducing kernel Hilbert space (RKHS), is the need for updating a growing number of parameters as time iterations evolve. Besides complexity, this leads to an increased need of communication resources, in a distributed setting. In contrast, the proposed method approximates the solution as a fixed-size vector (of larger dimension than the input space) using Random Fourier Features. This paves the way to use standard linear combine-then-adapt techniques. To the best of our knowledge, this is the first time that a complete protocol for distributed online learning in RKHS is presented. Conditions for asymptotic convergence and boundness of the networkwise regret are also provided. The simulated tests illustrate the performance of the proposed scheme.

  11. The responsible use of online social networking: who should mentor medical students.

    Science.gov (United States)

    Patel, Pradip D; Roberts, John L; Miller, Karen Hughes; Ziegler, Craig; Ostapchuk, Michael

    2012-01-01

    As medical students become more active in online social networking (OSN), there are increasing concerns regarding violations of patient privacy and a lack of professionalism. Students need to be mentored, but who is best suited to the task? We hypothesized that residents are closer to students in usage and attitudes toward online communication than are faculty. If so, they would be more credible as mentors. We surveyed faculty (N = 16), 1st-year residents (N = 120), and 3rd-year medical students (N = 130) to compare attitudes about OSN and the online usage patterns. We found residents to be more like students in usage patterns of personal electronic media and in their choice of the mentoring techniques that should be used. Residents say they were not prepared to mentor students without additional guidance but were more confident than faculty members that they had the knowledge to do so.

  12. Original research: online social networking patterns among adolescents, young adults, and sexual offenders.

    Science.gov (United States)

    Dowdell, Elizabeth B; Burgess, Ann W; Flores, J Robert

    2011-07-01

    The use of online social networks like Facebook continues to increase rapidly among all age groups and segments of our society, presenting new opportunities for the exchange of sexual information as well as for potentially unsafe encounters between predators and the vulnerable or young. This study surveyed middle school, high school, and college-age students, as well as sexual offenders, regarding their use of social networking sites in order to provide information to better focus education and prevention efforts from nurses and other health care providers. Written questionnaires asking about various characteristics of participants' use of social networking sites were distributed to each group and filled out by 404 middle school students, 2,077 high school students, 1,284 students drawn from five traditional four-year colleges, and 466 adults who had committed either an Internet sexual offense or a hands-on sexual offense (in some cases both). Notable findings emerging from our analysis of the questionnaire responses included the following: offenders and students both frequent social networking sites, although at the time of the study offenders reported that they preferred Myspace and students that they preferred Facebook; nearly two-thirds of the Internet offenders said they'd initiated the topic of sex in their first chat session; more than half of the Internet offenders disguised their identity when online; most Internet offenders we surveyed said they preferred communicating with teenage girls rather than teenage boys; high school students' experience with "sexting" (sharing nude photos of themselves or others on cell phones or online) differed significantly according to their sex; a small number of students are being threatened and assaulted by people they meet online; avatar sites such as Second Life were used both by students and offenders, with both child molesters and Internet offenders expressing interest in Second Life. The use of the Internet presents

  13. Severe Accident Management System On-line Network SAMSON

    International Nuclear Information System (INIS)

    Silverman, Eugene B.

    2004-01-01

    SAMSON is a computational tool used by accident managers in the Technical Support Centers (TSC) and Emergency Operations Facilities (EOF) in the event of a nuclear power plant accident. SAMSON examines over 150 status points monitored by nuclear power plant process computers during a severe accident and makes predictions about when core damage, support plate failure, and reactor vessel failure will occur. These predictions are based on the current state of the plant assuming that all safety equipment not already operating will fail. SAMSON uses expert systems, as well as neural networks trained with the back propagation learning algorithms to make predictions. Training on data from an accident analysis code (MAAP - Modular Accident Analysis Program) allows SAMSON to associate different states in the plant with different times to critical failures. The accidents currently recognized by SAMSON include steam generator tube ruptures (SGTRs), with breaks ranging from one tube to eight tubes, and loss of coolant accidents (LOCAs), with breaks ranging from 0.0014 square feet (1.30 cm 2 ) in size to breaks 3.0 square feet in size (2800 cm 2 ). (author)

  14. Modeling geo-homopholy in online social networks for population distribution projection

    Directory of Open Access Journals (Sweden)

    Yuanxing Zhang

    2017-09-01

    Full Text Available Purpose – Projecting the population distribution in geographical regions is important for many applications such as launching marketing campaigns or enhancing the public safety in certain densely populated areas. Conventional studies require the collection of people’s trajectory data through offline means, which is limited in terms of cost and data availability. The wide use of online social network (OSN apps over smartphones has provided the opportunities of devising a lightweight approach of conducting the study using the online data of smartphone apps. This paper aims to reveal the relationship between the online social networks and the offline communities, as well as to project the population distribution by modeling geo-homophily in the online social networks. Design/methodology/approach – In this paper, the authors propose the concept of geo-homophily in OSNs to determine how much the data of an OSN can help project the population distribution in a given division of geographical regions. Specifically, the authors establish a three-layered theoretic framework that first maps the online message diffusion among friends in the OSN to the offline population distribution over a given division of regions via a Dirichlet process and then projects the floating population across the regions. Findings – By experiments over large-scale OSN data sets, the authors show that the proposed prediction models have a high prediction accuracy in characterizing the process of how the population distribution forms and how the floating population changes over time. Originality/value – This paper tries to project population distribution by modeling geo-homophily in OSNs.

  15. Online variational Bayesian filtering-based mobile target tracking in wireless sensor networks.

    Science.gov (United States)

    Zhou, Bingpeng; Chen, Qingchun; Li, Tiffany Jing; Xiao, Pei

    2014-11-11

    The received signal strength (RSS)-based online tracking for a mobile node in wireless sensor networks (WSNs) is investigated in this paper. Firstly, a multi-layer dynamic Bayesian network (MDBN) is introduced to characterize the target mobility with either directional or undirected movement. In particular, it is proposed to employ the Wishart distribution to approximate the time-varying RSS measurement precision's randomness due to the target movement. It is shown that the proposed MDBN offers a more general analysis model via incorporating the underlying statistical information of both the target movement and observations, which can be utilized to improve the online tracking capability by exploiting the Bayesian statistics. Secondly, based on the MDBN model, a mean-field variational Bayesian filtering (VBF) algorithm is developed to realize the online tracking of a mobile target in the presence of nonlinear observations and time-varying RSS precision, wherein the traditional Bayesian filtering scheme cannot be directly employed. Thirdly, a joint optimization between the real-time velocity and its prior expectation is proposed to enable online velocity tracking in the proposed online tacking scheme. Finally, the associated Bayesian Cramer-Rao Lower Bound (BCRLB) analysis and numerical simulations are conducted. Our analysis unveils that, by exploiting the potential state information via the general MDBN model, the proposed VBF algorithm provides a promising solution to the online tracking of a mobile node in WSNs. In addition, it is shown that the final tracking accuracy linearly scales with its expectation when the RSS measurement precision is time-varying.

  16. Emergence of scale-free close-knit friendship structure in online social networks.

    Directory of Open Access Journals (Sweden)

    Ai-Xiang Cui

    Full Text Available Although the structural properties of online social networks have attracted much attention, the properties of the close-knit friendship structures remain an important question. Here, we mainly focus on how these mesoscale structures are affected by the local and global structural properties. Analyzing the data of four large-scale online social networks reveals several common structural properties. It is found that not only the local structures given by the indegree, outdegree, and reciprocal degree distributions follow a similar scaling behavior, the mesoscale structures represented by the distributions of close-knit friendship structures also exhibit a similar scaling law. The degree correlation is very weak over a wide range of the degrees. We propose a simple directed network model that captures the observed properties. The model incorporates two mechanisms: reciprocation and preferential attachment. Through rate equation analysis of our model, the local-scale and mesoscale structural properties are derived. In the local-scale, the same scaling behavior of indegree and outdegree distributions stems from indegree and outdegree of nodes both growing as the same function of the introduction time, and the reciprocal degree distribution also shows the same power-law due to the linear relationship between the reciprocal degree and in/outdegree of nodes. In the mesoscale, the distributions of four closed triples representing close-knit friendship structures are found to exhibit identical power-laws, a behavior attributed to the negligible degree correlations. Intriguingly, all the power-law exponents of the distributions in the local-scale and mesoscale depend only on one global parameter, the mean in/outdegree, while both the mean in/outdegree and the reciprocity together determine the ratio of the reciprocal degree of a node to its in/outdegree. Structural properties of numerical simulated networks are analyzed and compared with each of the four

  17. Emergence of scale-free close-knit friendship structure in online social networks.

    Science.gov (United States)

    Cui, Ai-Xiang; Zhang, Zi-Ke; Tang, Ming; Hui, Pak Ming; Fu, Yan

    2012-01-01

    Although the structural properties of online social networks have attracted much attention, the properties of the close-knit friendship structures remain an important question. Here, we mainly focus on how these mesoscale structures are affected by the local and global structural properties. Analyzing the data of four large-scale online social networks reveals several common structural properties. It is found that not only the local structures given by the indegree, outdegree, and reciprocal degree distributions follow a similar scaling behavior, the mesoscale structures represented by the distributions of close-knit friendship structures also exhibit a similar scaling law. The degree correlation is very weak over a wide range of the degrees. We propose a simple directed network model that captures the observed properties. The model incorporates two mechanisms: reciprocation and preferential attachment. Through rate equation analysis of our model, the local-scale and mesoscale structural properties are derived. In the local-scale, the same scaling behavior of indegree and outdegree distributions stems from indegree and outdegree of nodes both growing as the same function of the introduction time, and the reciprocal degree distribution also shows the same power-law due to the linear relationship between the reciprocal degree and in/outdegree of nodes. In the mesoscale, the distributions of four closed triples representing close-knit friendship structures are found to exhibit identical power-laws, a behavior attributed to the negligible degree correlations. Intriguingly, all the power-law exponents of the distributions in the local-scale and mesoscale depend only on one global parameter, the mean in/outdegree, while both the mean in/outdegree and the reciprocity together determine the ratio of the reciprocal degree of a node to its in/outdegree. Structural properties of numerical simulated networks are analyzed and compared with each of the four real networks. This

  18. Robustness analysis of the Zhang neural network for online time-varying quadratic optimization

    International Nuclear Information System (INIS)

    Zhang Yunong; Ruan Gongqin; Li Kene; Yang Yiwen

    2010-01-01

    A general type of recurrent neural network (termed as Zhang neural network, ZNN) has recently been proposed by Zhang et al for the online solution of time-varying quadratic-minimization (QM) and quadratic-programming (QP) problems. Global exponential convergence of the ZNN could be achieved theoretically in an ideal error-free situation. In this paper, with the normal differentiation and dynamics-implementation errors considered, the robustness properties of the ZNN model are investigated for solving these time-varying problems. In addition, linear activation functions and power-sigmoid activation functions could be applied to such a perturbed ZNN model. Both theoretical-analysis and computer-simulation results demonstrate the good ZNN robustness and superior performance for online time-varying QM and QP problem solving, especially when using power-sigmoid activation functions.

  19. Adaptive online inverse control of a shape memory alloy wire actuator using a dynamic neural network

    International Nuclear Information System (INIS)

    Mai, Huanhuan; Liao, Xiaofeng; Song, Gangbing

    2013-01-01

    Shape memory alloy (SMA) actuators exhibit severe hysteresis, a nonlinear behavior, which complicates control strategies and limits their applications. This paper presents a new approach to controlling an SMA actuator through an adaptive inverse model based controller that consists of a dynamic neural network (DNN) identifier, a copy dynamic neural network (CDNN) feedforward term and a proportional (P) feedback action. Unlike fixed hysteresis models used in most inverse controllers, the proposed one uses a DNN to identify online the relationship between the applied voltage to the actuator and the displacement (the inverse model). Even without a priori knowledge of the SMA hysteresis and without pre-training, the proposed controller can precisely control the SMA wire actuator in various tracking tasks by identifying online the inverse model of the SMA actuator. Experiments were conducted, and experimental results demonstrated real-time modeling capabilities of DNN and the performance of the adaptive inverse controller. (paper)

  20. Adaptive online inverse control of a shape memory alloy wire actuator using a dynamic neural network

    Science.gov (United States)

    Mai, Huanhuan; Song, Gangbing; Liao, Xiaofeng

    2013-01-01

    Shape memory alloy (SMA) actuators exhibit severe hysteresis, a nonlinear behavior, which complicates control strategies and limits their applications. This paper presents a new approach to controlling an SMA actuator through an adaptive inverse model based controller that consists of a dynamic neural network (DNN) identifier, a copy dynamic neural network (CDNN) feedforward term and a proportional (P) feedback action. Unlike fixed hysteresis models used in most inverse controllers, the proposed one uses a DNN to identify online the relationship between the applied voltage to the actuator and the displacement (the inverse model). Even without a priori knowledge of the SMA hysteresis and without pre-training, the proposed controller can precisely control the SMA wire actuator in various tracking tasks by identifying online the inverse model of the SMA actuator. Experiments were conducted, and experimental results demonstrated real-time modeling capabilities of DNN and the performance of the adaptive inverse controller.

  1. Dimensionality and effects of information motivation on users’ online social network advertising acceptance

    Directory of Open Access Journals (Sweden)

    IMRAN ANWAR MIR

    2018-04-01

    Full Text Available Social media has produced substantial changes in the communication landscape. Online social network sites (SNS grew as a common platform for online social interaction. SNS firms generate revenue from the advertising appearing on SNS. Their survival depends on users’ approval of such social network advertising (SNA. Marketing literature indicates that users accept advertising if it is consistent with their motivations for using social media. Information seeking is the most recognized SNS motivation. Yet, research on evaluating the influence of SNS information motivation on users’ approval of SNA is scarce. Based on SNS uses and gratifications theory, this study proposes a multidimensional model that shows the influence of SNS information motivation on users’ approval of SNA.

  2. Radiology online: information, education, and networking--a summary of the 2012 Intersociety Committee Summer Conference.

    Science.gov (United States)

    Dodd, Gerald D; Naeger, David M

    2013-05-01

    The "new online" (Web 2.0) world is evolving rapidly, and the digital information, education, and networking resources available to radiologists have exploded over the past 2 decades. The 2012 Intersociety Committee Summer Conference attendees explored the online resources that have been produced by societies, universities, and commercial entities. Specific attention was given to identifying the best products and packaging them in tablet computers for use by residents and practicing radiologists. The key functions of social networking websites and the possible roles they can play in radiology were explored as well. It was the consensus of the attendees that radiologic digital resources and portable electronic devices have matured to the point that they should become an integral part of our educational programs and clinical practice. Copyright © 2013 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  3. Nationwide online social networking for cardiovascular care in Korea using Facebook.

    Science.gov (United States)

    Kim, Changsun; Kang, Bo Seung; Choi, Hyuk Joong; Lee, Young Joo; Kang, Gu Hyun; Choi, Wook Jin; Kwon, In Ho

    2014-01-01

    To examine the use of online social networking for cardiovascular care using Facebook. All posts and comments in a Facebook group between June 2011 and May 2012 were reviewed, and a survey was conducted. A total of 298 members participated. Of the 277 wall posts, 26.7% were question posts requesting rapid replies, and 50.5% were interesting cases shared with other members. The median response time for the question posts was 16 min (IQR 8-47), which tended to decrease as more members joined the group. Many members (37.4%) accessed the group more than once a day, and more than half (64%) monitored the group posts in real time with automatic notifications of new posts. Most members expressed confidence in the content posted. Facebook enables online social networking between physicians in near-real time and appears to be a useful tool for physicians to share clinical experience and request assistance in decision-making.

  4. Interprofessional Student Perspectives of Online Social Networks in Health and Business Education.

    Science.gov (United States)

    Doyle, Glynda; Jones, Cyri; Currie, Leanne

    2016-01-01

    The education sector is experiencing unprecedented change with the increasing use by students of mobile devices, social networks and e-portfolios as they prepare for future positions in the workforce. The purpose of this study was to examine student's preferences around these technologies. A mixed methods research strategy was used with an initial online survey using 29 Likert scale style questions to students from the School of Health Sciences and the School of Business at the British Columbia Institute of Technology (BCIT). Descriptive statistics and ANOVAs were performed to examine if there were any differences between groups regarding their overall responses to the survey questions. Content analysis was used for qualitative focus group data. Overall, students (n = 260) were enthusiastic about technology but wary of cost, lack of choice, increased workload and faculty involvement in their online social networks. Of note, students see significant value in face-to-face classroom time.

  5. Liking and hyperlinking: Community detection in online child sexual exploitation networks.

    Science.gov (United States)

    Westlake, Bryce G; Bouchard, Martin

    2016-09-01

    The online sexual exploitation of children is facilitated by websites that form virtual communities, via hyperlinks, to distribute images, videos, and other material. However, how these communities form, are structured, and evolve over time is unknown. Collected using a custom-designed webcrawler, we begin from known child sexual exploitation (CE) seed websites and follow hyperlinks to connected, related, websites. Using a repeated measure design we analyze 10 networks of 300 + websites each - over 4.8 million unique webpages in total, over a period of 60 weeks. Community detection techniques reveal that CE-related networks were dominated by two large communities hosting varied material -not necessarily matching the seed website. Community stability, over 60 weeks, varied across networks. Reciprocity in hyperlinking between community members was substantially higher than within the full network, however, websites were not more likely to connect to homogeneous-content websites. Copyright © 2016 Elsevier Inc. All rights reserved.

  6. CONSUMER OPINIONS TOWARDS ONLINE MARKETING COMMUNICATION AND ADVERTISING ON SOCIAL NETWORKS

    Directory of Open Access Journals (Sweden)

    GHEORGHE ORZAN

    2012-05-01

    Full Text Available On the Internet, a medium that has already proven its effectiveness in marketing activities, changes take place with astonishing speed. The recent explosion of social networking applications and their number of users has captured the marketers’ attention. Companies have started to rethink their relationships with consumers and adapt to the new online world. In this virtual world of social networks the public is the key element. Consumers perceive the social network as a personal space where they control the content. They decide on their own what they want to see and share with others. Thus, in order to manage marketing communications effectively, marketers must know the consumers’ opinions towards their presence in social networks.

  7. Comparing social factors affecting recommender decisions in online and educational social network

    Science.gov (United States)

    MartÍn, Estefanía; Hernán-Losada, Isidoro; Haya, Pablo A.

    2016-01-01

    In the educational context, there is an increasing interest in learning networks. Recommender systems (RSs) can play an important role in achieving educational objectives. Although we can find many papers focused on recommendation techniques and algorithms, in general, less attention has been dedicated to social factors that influence the recommendation process. This process could be improved if we had a deeper understanding of the social factors that influence the quality or validity of a suggestion made by the RS. This work elucidates and analyses the social factors that influence the design and decision-making process of RSs. We conducted a survey in which 126 undergraduate students were asked to extract which are the main factors for improving suggestions when they are interacting with an Online Social Network (OSN) or in an Educational Social Network (ESN). The results show that different factors have to be considered depending on the type of network.

  8. A Game Theoretic Approach for Modeling Privacy Settings of an Online Social Network

    Directory of Open Access Journals (Sweden)

    Jundong Chen

    2014-05-01

    Full Text Available Users of online social networks often adjust their privacy settings to control how much information on their profiles is accessible to other users of the networks. While a variety of factors have been shown to affect the privacy strategies of these users, very little work has been done in analyzing how these factors influence each other and collectively contribute towards the users’ privacy strategies. In this paper, we analyze the influence of attribute importance, benefit, risk and network topology on the users’ attribute disclosure behavior by introducing a weighted evolutionary game model. Results show that: irrespective of risk, users aremore likely to reveal theirmost important attributes than their least important attributes; when the users’ range of influence is increased, the risk factor plays a smaller role in attribute disclosure; the network topology exhibits a considerable effect on the privacy in an environment with risk.

  9. An Empirical Study Of User Acceptance Of Online Social Networks Marketing

    Directory of Open Access Journals (Sweden)

    Olumayowa Mulero

    2013-07-01

    Full Text Available The explosion of Internet usage has drawn the attention of researchers towards online Social Networks Marketing (SNM. Research has shown that a number of the Internet users are distrustful and indecisive, when it comes to the use of social networks marketing system. Therefore, there is a need for researchers to identify some of the factors that determine users’ acceptance of social networks marketing using Technology Acceptance Model (TAM. This study extended the Technology Acceptance Model theoretical framework to predict consumer acceptance of social networks marketing within Western Cape Province of South Africa. The research model was tested using data collected from 470 questionnaires and analysed using linear regression. The results showed that user intentions to use SNM are strongly and positively correlated with user acceptance of using SNM systems. Empirical results confirmed that perceived credibility and perceived usefulness are the strongest determinant in predicting user intentions to use SNM system.

  10. Interaction, Critical Thinking, and Social Network Analysis (SNA in Online Courses

    Directory of Open Access Journals (Sweden)

    Joan Thormann

    2013-07-01

    Full Text Available This study tried to ascertain a possible relationship between the number of student moderators (1, 2, and 3, online interactions, and critical thinking of K-12 educators enrolled in an online course that was taught from a constructivist approach. The course topic was use of technology in special education. Social network analysis (SNA and measures of critical thinking (Newman, Webb, & Cochrane, 1995 were used to research and assess if there was a difference in interaction and critical thinking between 1, 2, or 3 student moderators who facilitated a forum discussion of an assignment in an online course. The same course was repeated over three years. Each year either 1, 2, or 3 students moderated. The analysis indicated more discussion per non-moderating student with the three student moderated group. Using SNA we found that there was only one noticeable difference among the three groups which was in the value of network centralization. Using critical thinking measures the three student moderator group scored higher in five of the eight critical thinking categories. Variations in instructor presence in the online courses may have influenced these findings.

  11. Talking about your health to strangers: understanding the use of online social networks by patients

    Science.gov (United States)

    Colineau, Nathalie; Paris, Cécile

    2010-04-01

    The internet has become a participatory place where everyone can contribute and interact with others. In health in particular, social media have changed traditional patient-physician relationships. Patients are organising themselves in groups, sharing observations and helping each other, although there is still little evidence of the effectiveness of these online communities on people's health. To understand why and how people use health-related sites, we studied these sites and identified three dimensions characterising most of them: informational/supportive; general/focused; and new relationships/existing ones. We conducted an online survey about the use of health-related social networking (SN) sites and learnt that, consistent with previous research, most patients were seeking information about their medical condition online, while, at the same time, still interacting with health professionals to talk about sensitive information and complex issues. We also found that, while people's natural social network played an important role for emotional support, sometimes, people chose to not involve their family, but instead interact with peers online because of their perceived support and ability to understand someone's experience, and also to maintain a comfortable emotional distance. Finally, our results show that people using general SN sites do not necessarily use health-related sites and vice versa.

  12. Transputer networks for the on-line analysis of fine-grained electromagnetic calorimeter data

    International Nuclear Information System (INIS)

    Girotto, G.L.; Lanceri, L.; Scuri, F.; Zoppolato, E.

    1994-01-01

    Transputer networks, designed to perform parallel computations, are well suited for data acquisition, on-line analysis and second level trigger tasks in high energy physics experiments. Some simple algorithms for the analysis of fine-grained electromagnetic calorimeter data were implemented on two types of transputer networks and tested on real and simulated data from a silicon-tungsten calorimeter. Results are presented on the processing speed, measured in a test setup, and extrapolations to a full size detector and data acquisition system are discussed. ((orig.))

  13. Design to Thrive Creating Social Networks and Online Communities that Last

    CERN Document Server

    Howard, Tharon W

    2010-01-01

    Social networks and online communities are reshaping the way people communicate, both in their personal and professional lives. What makes some succeed and others fail? What draws a user in? What makes them join? What keeps them coming back? Entrepreneurs and businesses are turning to user experience practitioners to figure this out. Though they are well-equipped to evaluate and create a variety of interfaces, social networks require a different set of design principles and ways of thinking about the user in order to be successful. .. .. Design to Thrive presents tried and tested design method

  14. jSquid: a Java applet for graphical on-line network exploration.

    Science.gov (United States)

    Klammer, Martin; Roopra, Sanjit; Sonnhammer, Erik L L

    2008-06-15

    jSquid is a graph visualization tool for exploring graphs from protein-protein interaction or functional coupling networks. The tool was designed for the FunCoup web site, but can be used for any similar network exploring purpose. The program offers various visualization and graph manipulation techniques to increase the utility for the user. jSquid is available for direct usage and download at http://jSquid.sbc.su.se including source code under the GPLv3 license, and input examples. It requires Java version 5 or higher to run properly. erik.sonnhammer@sbc.su.se Supplementary data are available at Bioinformatics online.

  15. Popular Topics Spread Faster: New Dimension for Influence Propagation in Online Social Networks

    OpenAIRE

    Pan, Tianyi; Kuhnle, Alan; Li, Xiang; Thai, My T.

    2017-01-01

    Information can propagate among Online Social Network (OSN) users at a high speed, which makes the OSNs become important platforms for viral marketing. Although the viral marketing related problems in OSNs have been extensively studied in the past decade, the existing works all assume known propagation rates and are not able to solve the scenario when the rates may dynamically increase for popular topics. In this paper, we propose a novel model, Dynamic Influence Propagation (DIP), which allo...

  16. Online Sequence Training of Recurrent Neural Networks with Connectionist Temporal Classification

    OpenAIRE

    Hwang, Kyuyeon; Sung, Wonyong

    2015-01-01

    Connectionist temporal classification (CTC) based supervised sequence training of recurrent neural networks (RNNs) has shown great success in many machine learning areas including end-to-end speech and handwritten character recognition. For the CTC training, however, it is required to unroll (or unfold) the RNN by the length of an input sequence. This unrolling requires a lot of memory and hinders a small footprint implementation of online learning or adaptation. Furthermore, the length of tr...

  17. Interaction patterns of nurturant support exchanged in online health social networking.

    Science.gov (United States)

    Chuang, Katherine Y; Yang, Christopher C

    2012-05-03

    Expressing emotion in online support communities is an important aspect of enabling e-patients to connect with each other and expand their social resources. Indirectly it increases the amount of support for coping with health issues. Exploring the supportive interaction patterns in online health social networking would help us better understand how technology features impacts user behavior in this context. To build on previous research that identified different types of social support in online support communities by delving into patterns of supportive behavior across multiple computer-mediated communication formats. Each format combines different architectural elements, affecting the resulting social spaces. Our research question compared communication across different formats of text-based computer-mediated communication provided on the MedHelp.org health social networking environment. We identified messages with nurturant support (emotional, esteem, and network) across three different computer-mediated communication formats (forums, journals, and notes) of an online support community for alcoholism using content analysis. Our sample consisted of 493 forum messages, 423 journal messages, and 1180 notes. Nurturant support types occurred frequently among messages offering support (forum comments: 276/412 messages, 67.0%; journal posts: 65/88 messages, 74%; journal comments: 275/335 messages, 82.1%; and notes: 1002/1180 messages, 84.92%), but less often among messages requesting support. Of all the nurturing supports, emotional (ie, encouragement) appeared most frequently, with network and esteem support appearing in patterns of varying combinations. Members of the Alcoholism Community appeared to adapt some traditional face-to-face forms of support to their needs in becoming sober, such as provision of encouragement, understanding, and empathy to one another. The computer-mediated communication format may have the greatest influence on the supportive interactions

  18. Pharmacy faculty members' perspectives on the student/faculty relationship in online social networks.

    Science.gov (United States)

    Metzger, Anne H; Finley, Kristen N; Ulbrich, Timothy R; McAuley, James W

    2010-12-15

    To describe pharmacy faculty members' use of the online social network Facebook and compare the perspectives of faculty members with and without Facebook profiles regarding student/faculty relationships. An electronic survey instrument was sent to full-time faculty members (n = 183) at 4 colleges of pharmacy in Ohio seeking their opinions on student/faculty relationships on Facebook. If respondents answered "yes" to having a Facebook profile, they were asked 14 questions on aspects of being "friends" with students. If respondents answered "no," they were asked 4 questions. Of the 95 respondents (52%) to the survey instrument, 44 faculty members (46%) had a Facebook profile, while 51 faculty members (54%) did not. Those who had a profile had been faculty members for an average of 8.6 years, versus 11.4 years for those who did not have a Facebook profile. Seventy-nine percent of faculty members who used Facebook were not "friends" with their students. The majority of respondents reported that they would decline/ignore a "friend" request from a student, or decline until after the student graduated. Although a limited number of faculty members had used Facebook for online discussions, teaching purposes, or student organizations, the majority of universities did not have policies on the use of social networking sites. Online social network sites are used widely by students and faculty members, which may raise questions regarding professionalism and appropriate faculty/student relationships. Further research should address the student/preceptor relationship, other online social networking sites, and whether students are interested in using these sites within the classroom and/or professional organizations.

  19. Frequency of Victimization Experiences and Well-Being Among Online, Offline, and Combined Victims on Social Online Network Sites of German Children and Adolescents.

    Science.gov (United States)

    Glüer, Michael; Lohaus, Arnold

    2015-01-01

    Victimization is associated with negative developmental outcomes in childhood and adolescence. However, previous studies have provided mixed results regarding the association between offline and online victimization and indicators of social, psychological, and somatic well-being. In this study, we investigated 1,890 German children and adolescents (grades 5-10, mean age = 13.9; SD = 2.1) with and without offline or online victimization experiences who participated in a social online network (SNS). Online questionnaires were used to assess previous victimization (offline, online, combined, and without), somatic and psychological symptoms, self-esteem, and social self-concept (social competence, resistance to peer influence, esteem by others). In total, 1,362 (72.1%) children and adolescents reported being a member of at least one SNS, and 377 students (28.8%) reported previous victimization. Most children and adolescents had offline victimization experiences (17.5%), whereas 2.7% reported online victimization, and 8.6% reported combined experiences. Girls reported more online and combined victimization, and boys reported more offline victimization. The type of victimization (offline, online, combined) was associated with increased reports of psychological and somatic symptoms, lower self-esteem and esteem by others, and lower resistance to peer influences. The effects were comparable for the groups with offline and online victimization. They were, however, increased in the combined group in comparison to victims with offline experiences alone.

  20. Fast Flux Watch: A mechanism for online detection of fast flux networks

    Directory of Open Access Journals (Sweden)

    Basheer N. Al-Duwairi

    2014-07-01

    Full Text Available Fast flux networks represent a special type of botnets that are used to provide highly available web services to a backend server, which usually hosts malicious content. Detection of fast flux networks continues to be a challenging issue because of the similar behavior between these networks and other legitimate infrastructures, such as CDNs and server farms. This paper proposes Fast Flux Watch (FF-Watch, a mechanism for online detection of fast flux agents. FF-Watch is envisioned to exist as a software agent at leaf routers that connect stub networks to the Internet. The core mechanism of FF-Watch is based on the inherent feature of fast flux networks: flux agents within stub networks take the role of relaying client requests to point-of-sale websites of spam campaigns. The main idea of FF-Watch is to correlate incoming TCP connection requests to flux agents within a stub network with outgoing TCP connection requests from the same agents to the point-of-sale website. Theoretical and traffic trace driven analysis shows that the proposed mechanism can be utilized to efficiently detect fast flux agents within a stub network.

  1. Online and social networking interventions for the treatment of depression in young people: a systematic review.

    Science.gov (United States)

    Rice, Simon M; Goodall, Joanne; Hetrick, Sarah E; Parker, Alexandra G; Gilbertson, Tamsyn; Amminger, G Paul; Davey, Christopher G; McGorry, Patrick D; Gleeson, John; Alvarez-Jimenez, Mario

    2014-09-16

    Major depression accounts for the greatest burden of all diseases globally. The peak onset of depression occurs between adolescence and young adulthood, and for many individuals, depression displays a relapse-remitting and increasingly severe course. Given this, the development of cost-effective, acceptable, and population-focused interventions for depression is critical. A number of online interventions (both prevention and acute phase) have been tested in young people with promising results. As these interventions differ in content, clinician input, and modality, it is important to identify key features (or unhelpful functions) associated with treatment outcomes. A systematic review of the research literature was undertaken. The review was designed to focus on two aspects of online intervention: (1) standard approaches evaluating online intervention content in randomized controlled designs (Section 1), and (2) second-generation online interventions and services using social networking (eg, social networking sites and online support groups) in any type of research design (Section 2). Two specific literature searches were undertaken. There was no date range specified. The Section 1 search, which focused on randomized controlled trials, included only young people (12-25 years) and yielded 101 study abstracts, of which 15 met the review inclusion criteria. The Section 2 search, which included all study design types and was not restricted in terms of age, yielded 358 abstracts, of which 22 studies met the inclusion criteria. Information about the studies and their findings were extracted and tabulated for review. The 15 studies identified in Section 1 described 10 trials testing eight different online interventions, all of which were based on a cognitive behavioral framework. All but one of the eight identified studies reported positive results; however, only five of the 15 studies used blinded interviewer administered outcomes with most trials using self-report data

  2. Towards Assisted Moderation in Online Healthcare Social Networks: Improving Trust in YouTube Searches.

    Science.gov (United States)

    Cañon, Daniel E; Lopez, Diego M; Blobel, Bernd

    2014-01-01

    Moderation of content in online Health Social Networks (HSN) is critical because information is not only published and produced by experts or health professionals, but also by users of that information. The objective of this paper is to propose a semi-automatic moderation Web Service for assessing the quality (trustworthiness) of health-related videos published on the YouTube social network. The service is relevant for moderators or community managers, who get enabled to control the quality of videos published on their online HSN sites. The HealthTrust metric was selected as the metric to be implemented in the service in order to support the assessment of trustworthiness of videos in Online HSN. The service is a RESTful service which can be integrated into open source Virtual Social Network Platforms, therefore improving trust in the process of searching and publishing content extracted from YouTube. A preliminary pilot evaluation in a simple use case demonstrated that the relevance of videos retrieved using the moderation service was higher compared to the relevance of the videos retrieved using the YouTube search engine.

  3. Online Academic Networks as Knowledge Brokers: The Mediating Role of Organizational Support

    Directory of Open Access Journals (Sweden)

    Elena-Mădălina Vătămănescu

    2018-04-01

    Full Text Available Placing online academic networks in the framework of social, cultural and institutional “deterritorialization,” the current paper aims at investigating the functionality of these new forms of transnational and trans-organizational aggregations as knowledge brokers. The emphasis is laid on the influence of human collective intelligence and consistent knowledge flows on research innovation, considering the role of organizational support within higher education systems. In this respect, the research relied on a questionnaire-based survey with 140 academics from European emerging countries, the data collected being processed via a partial least squares structural equation modelling technique. Evidence was brought that, as knowledge brokers, online academic networks are systems aimed to support the access to human collective intelligence and consistent knowledge flows which exert a positive influence on research innovation, both directly and indirectly, by means of formal and informal organizational support. As facilitators of collaborative environments for individuals with specialized knowledge, competence, expertise and experience, online academic networks have set themselves up as an agora for academics worldwide and as an outlet for their acumen and literacy.

  4. Words analysis of online Chinese news headlines about trending events: a complex network perspective.

    Science.gov (United States)

    Li, Huajiao; Fang, Wei; An, Haizhong; Huang, Xuan

    2015-01-01

    Because the volume of information available online is growing at breakneck speed, keeping up with meaning and information communicated by the media and netizens is a new challenge both for scholars and for companies who must address public relations crises. Most current theories and tools are directed at identifying one website or one piece of online news and do not attempt to develop a rapid understanding of all websites and all news covering one topic. This paper represents an effort to integrate statistics, word segmentation, complex networks and visualization to analyze headlines' keywords and words relationships in online Chinese news using two samples: the 2011 Bohai Bay oil spill and the 2010 Gulf of Mexico oil spill. We gathered all the news headlines concerning the two trending events in the search results from Baidu, the most popular Chinese search engine. We used Simple Chinese Word Segmentation to segment all the headlines into words and then took words as nodes and considered adjacent relations as edges to construct word networks both using the whole sample and at the monthly level. Finally, we develop an integrated mechanism to analyze the features of words' networks based on news headlines that can account for all the keywords in the news about a particular event and therefore track the evolution of news deeply and rapidly.

  5. Words analysis of online Chinese news headlines about trending events: a complex network perspective.

    Directory of Open Access Journals (Sweden)

    Huajiao Li

    Full Text Available Because the volume of information available online is growing at breakneck speed, keeping up with meaning and information communicated by the media and netizens is a new challenge both for scholars and for companies who must address public relations crises. Most current theories and tools are directed at identifying one website or one piece of online news and do not attempt to develop a rapid understanding of all websites and all news covering one topic. This paper represents an effort to integrate statistics, word segmentation, complex networks and visualization to analyze headlines' keywords and words relationships in online Chinese news using two samples: the 2011 Bohai Bay oil spill and the 2010 Gulf of Mexico oil spill. We gathered all the news headlines concerning the two trending events in the search results from Baidu, the most popular Chinese search engine. We used Simple Chinese Word Segmentation to segment all the headlines into words and then took words as nodes and considered adjacent relations as edges to construct word networks both using the whole sample and at the monthly level. Finally, we develop an integrated mechanism to analyze the features of words' networks based on news headlines that can account for all the keywords in the news about a particular event and therefore track the evolution of news deeply and rapidly.

  6. Social comparison 2.0: examining the effects of online profiles on social-networking sites.

    Science.gov (United States)

    Haferkamp, Nina; Krämer, Nicole C

    2011-05-01

    Through their features--such as profile photographs or the personal vita--online profiles on social-networking sites offer a perfect basis for social comparison processes. By looking at the profile photograph, the user gains an impression of a person's physical attractiveness, and the user's vita shows which career path the person is pursuing. Against the background of Festinger's Social Comparison Theory, the focus of this research is on the effects of online profiles on their recipients. Therefore, qualitative interviews (N = 12) and two online experiments were conducted in which virtual online profiles of either physically attractive or unattractive persons (N = 93) and profiles of users with either high or low occupational attainment (N = 103) were presented to the participants. Although qualitative interviews did not initially give reason to expect online profiles to constitute a basis for comparison processes, results of the experiments proved otherwise. The first study indicates that recipients have a more negative body image after looking at beautiful users than persons who were shown the less attractive profile pictures. Male participants of the second study, who were confronted with profiles of successful males, showed a higher perceived discrepancy between their current career status and an ideal vita than male participants who looked at profiles of less successful persons.

  7. Finding The Most Important Actor in Online Crowd by Social Network Analysis

    Science.gov (United States)

    Yuliana, I.; Santosa, P. I.; Setiawan, N. A.; Sukirman

    2017-02-01

    Billion of people create trillions of connections through social media every single day. The increasing use of social media has led to dramatic changes in the of way science, government, healthcare, entertainment and enterprise operate. Large-scale participation in Technology-Mediated Social Participation (TMSP) system has opened up incredible new opportunities to deploy online crowd. This descriptive-correlational research used social network analysis (SNA) on data gathered from Fanpage Facebook of Greenpeace Indonesia related to important critical issues, the bushfires in 2015. SNA identifies relations on each member by sociometrics parameter such as three centrality (degree, closeness and betweenesse) for measuring and finding the most important actor in the online community. This paper use Fruchterman Rein-gold algorithm to visualize the online community in a graph, while Clauset-Newman-Moore is a technique to identify groups in community. As the result found 3735 vertices related to actors, 6927 edges as relation, 14 main actors in size order and 22 groups in Greenpeace Indonesia online community. This research contributes to organize some information for Greenpeace Indonesia managing their potency in online community to identify human behaviour.

  8. Analysis of Context Dependence in Social Interaction Networks of a Massively Multiplayer Online Role-Playing Game

    OpenAIRE

    Son, Seokshin; Kang, Ah Reum; Kim, Hyun-chul; Kwon, Taekyoung; Park, Juyong; Kim, Huy Kang

    2012-01-01

    Rapid advances in modern computing and information technology have enabled millions of people to interact online via various social network and gaming services. The widespread adoption of such online services have made possible analysis of large-scale archival data containing detailed human interactions, presenting a very promising opportunity to understand the rich and complex human behavior. In collaboration with a leading global provider of Massively Multiplayer Online Role-Playing Games (...

  9. To View or Not To View: The Influence of Social Networks and Subjective Norms on Online Pornography Consumption

    Directory of Open Access Journals (Sweden)

    Wan-Ying Lin

    2012-06-01

    Full Text Available This study investigates the influence of social networks and subjective norms on an individual’s online pornography consumption. The empirical survey results of 324 voluntary participants indicated that the individual’s positive outcome evaluation was associated with a higher level of online pornography exposure. Social pressure also plays a significant, but negative, role in one’s viewing decision.

  10. Your Health Buddies Matter: Preferential Selection and Social Influence on Weight Management in an Online Health Social Network.

    Science.gov (United States)

    Meng, Jingbo

    2016-12-01

    A growing number of online social networks are designed with the intention to promote health by providing virtual space wherein individuals can seek and share information and support with similar others. Research has shown that real-world social networks have a significant influence on one's health behavior and outcomes. However, there is a dearth of studies on how individuals form social networks in virtual space and whether such online social networks exert any impact on individuals' health outcomes. Built on the Multi-Theoretical Multilevel (MTML) framework and drawing from literature on social influence, this study examined the mechanisms underlying the formation of an online health social network and empirically tested social influence on individual health outcomes through the network. Situated in a weight management social networking site, the study tracked a health buddy network of 709 users and their weight management activities and outcomes for 4 months. Actor-based modeling was used to test the joint dynamics of preferential selection and social influence among health buddies. The results showed that baseline, inbreeding, and health status homophily significantly predicted preferential selection of health buddies in the weight management social networking site, whereas self-interest in seeking experiential health information did not. The study also found peer influence of online health buddy networks on individual weight outcomes, such that an individual's odds of losing weight increased if, on average, the individual's health buddies were losing weight.

  11. PREDICTIVE CONTROL OF A BATCH POLYMERIZATION SYSTEM USING A FEEDFORWARD NEURAL NETWORK WITH ONLINE ADAPTATION BY GENETIC ALGORITHM

    OpenAIRE

    Cancelier, A.; Claumann, C. A.; Bolzan, A.; Machado, R. A. F.

    2016-01-01

    Abstract This study used a predictive controller based on an empirical nonlinear model comprising a three-layer feedforward neural network for temperature control of the suspension polymerization process. In addition to the offline training technique, an algorithm was also analyzed for online adaptation of its parameters. For the offline training, the network was statically trained and the genetic algorithm technique was used in combination with the least squares method. For online training, ...

  12. Configurations of using social networking sites and perceived online social capital among adults with and without disabilities

    OpenAIRE

    Viluckienė, Jolita; Ruškus, Jonas

    2017-01-01

    Drawing on nationally representative survey 2014 data, this article examines the implications of social networking sites (SNS) use and the relationship with perceived online social capital among Lithuanian adults with and without disabilities. By contributing to the wide academic discussion on the value of online and social networks for people with disabilities, this research shows that intensive participation on SNS (as Facebook) presupposes stronger affective and evaluative dimensions of so...

  13. Topical Network of Breast Cancer Information in a Korean American Online Community: A Semantic Network Analysis

    Science.gov (United States)

    Park, Min Sook; Park, Hyejin

    2016-01-01

    Introduction: Health information-seeking and sharing online has become immensely intertwined with day-to-day information-seeking of US immigrants with health concerns. Despite the consistent recognition of unique health needs among different US immigrant communities, little is known about the distinctive patterns and extent of health information…

  14. Social dilemmas in an online social network: The structure and evolution of cooperation

    International Nuclear Information System (INIS)

    Fu Feng; Chen Xiaojie; Liu Lianghuan; Wang Long

    2007-01-01

    We investigate two paradigms for studying the evolution of cooperation-Prisoner's Dilemma and Snowdrift game in an online friendship network, obtained from a social networking site. By structural analysis, it is revealed that the empirical social network has small-world and scale-free properties. Besides, it exhibits assortative mixing pattern. Then, we study the evolutionary version of the two types of games on it. It is found that cooperation is substantially promoted with small values of game matrix parameters in both games. Whereas the competent cooperators induced by the underlying network of contacts will be dramatically inhibited with increasing values of the game parameters. Further, we explore the role of assortativity in evolution of cooperation by random edge rewiring. We find that increasing amount of assortativity will to a certain extent diminish the cooperation level. We also show that connected large hubs are capable of maintaining cooperation. The evolution of cooperation on empirical networks is influenced by various network effects in a combined manner, compared with that on model networks. Our results can help understand the cooperative behaviors in human groups and society

  15. Online Expansion Technology for Dynamic Topology Changing ZigBee Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Md. Emdadul Haque

    2014-03-01

    Full Text Available In ZigBee, the router capable devices have restriction to accept a number of devices as children devices. A router capable device can not allow any new device to join as a child device if it reaches to the maximum capacity of children or depth limit. According to ZigBee specification each device has a permanent 64-bit MAC address. If a device joins a ZigBee network, it receives a short 16-bit MAC address from the parent device. If a device can not join a network, it isolates from the network and becomes an orphan node even though address spaces are available in the network. The orphan problem becomes worse when the topology of the network changes dynamically. In this paper we propose an online expansion technology to connect the maximum number of devices specially for dynamic topology changing ZigBee wireless sensor networks. The proposed technology shares available address spaces of the router devices to reduce the number of orphan nodes in the network.

  16. Social dilemmas in an online social network: The structure and evolution of cooperation

    Energy Technology Data Exchange (ETDEWEB)

    Fu Feng [Center for Systems and Control, College of Engineering, Peking University, Beijing 100871 (China); Department of Industrial Engineering and Management, College of Engineering, Peking University, Beijing 100871 (China)], E-mail: fufeng@pku.edu.cn; Chen Xiaojie; Liu Lianghuan [Center for Systems and Control, College of Engineering, Peking University, Beijing 100871 (China); Department of Industrial Engineering and Management, College of Engineering, Peking University, Beijing 100871 (China); Wang Long [Center for Systems and Control, College of Engineering, Peking University, Beijing 100871 (China); Department of Industrial Engineering and Management, College of Engineering, Peking University, Beijing 100871 (China)], E-mail: longwang@pku.edu.cn

    2007-11-05

    We investigate two paradigms for studying the evolution of cooperation-Prisoner's Dilemma and Snowdrift game in an online friendship network, obtained from a social networking site. By structural analysis, it is revealed that the empirical social network has small-world and scale-free properties. Besides, it exhibits assortative mixing pattern. Then, we study the evolutionary version of the two types of games on it. It is found that cooperation is substantially promoted with small values of game matrix parameters in both games. Whereas the competent cooperators induced by the underlying network of contacts will be dramatically inhibited with increasing values of the game parameters. Further, we explore the role of assortativity in evolution of cooperation by random edge rewiring. We find that increasing amount of assortativity will to a certain extent diminish the cooperation level. We also show that connected large hubs are capable of maintaining cooperation. The evolution of cooperation on empirical networks is influenced by various network effects in a combined manner, compared with that on model networks. Our results can help understand the cooperative behaviors in human groups and society.

  17. The research of development dynamics of electronic social networks for the effective advertisement of online shops in the segment of Ukrainian network business

    Directory of Open Access Journals (Sweden)

    O.I. Grabar

    2015-09-01

    Full Text Available The article presents the research results of development dynamics of the Ukrainian segment of different social networks in the global network. The general methods of creation and development of online shop are described. The methods of creation and development of marketing communications for online shops and their influence on the development of electronic business in Ukraine are presented. The article gives the detailed analysis of statistical data on age & gender related distribution of the Ukrainian segment of the biggest world social networks. The author also introduces new instruments for marketing communications worked out by every social network. The basic principles of advertisement campaign realization for online shops with the use of target audience of certain groups in social networks are generalized.

  18. Understanding Online Health Groups for Depression: Social Network and Linguistic Perspectives.

    Science.gov (United States)

    Xu, Ronghua; Zhang, Qingpeng

    2016-03-10

    Mental health problems have become increasingly prevalent in the past decade. With the advance of Web 2.0 technologies, social media present a novel platform for Web users to form online health groups. Members of online health groups discuss health-related issues and mutually help one another by anonymously revealing their mental conditions, sharing personal experiences, exchanging health information, and providing suggestions and support. The conversations in online health groups contain valuable information to facilitate the understanding of their mutual help behaviors and their mental health problems. We aimed to characterize the conversations in a major online health group for major depressive disorder (MDD) patients in a popular Chinese social media platform. In particular, we intended to explain how Web users discuss depression-related issues from the perspective of the social networks and linguistic patterns revealed by the members' conversations. Social network analysis and linguistic analysis were employed to characterize the social structure and linguistic patterns, respectively. Furthermore, we integrated both perspectives to exploit the hidden relations between them. We found an intensive use of self-focus words and negative affect words. In general, group members used a higher proportion of negative affect words than positive affect words. The social network of the MDD group for depression possessed small-world and scale-free properties, with a much higher reciprocity ratio and clustering coefficient value as compared to the networks of other social media platforms and classic network models. We observed a number of interesting relationships, either strong correlations or convergent trends, between the topological properties and linguistic properties of the MDD group members. (1) The MDD group members have the characteristics of self-preoccupation and negative thought content, according to Beck's cognitive theory of depression; (2) the social structure

  19. Mental disorder recovery correlated with centralities and interactions on an online social network

    Directory of Open Access Journals (Sweden)

    Xinpei Ma

    2015-08-01

    Full Text Available Recent research has established both a theoretical basis and strong empirical evidence that effective social behavior plays a beneficial role in the maintenance of physical and psychological well-being of people. To test whether social behavior and well-being are also associated in online communities, we studied the correlations between the recovery of patients with mental disorders and their behaviors in online social media. As the source of the data related to the social behavior and progress of mental recovery, we used PatientsLikeMe (PLM, the world’s first open-participation research platform for the development of patient-centered health outcome measures. We first constructed an online social network structure based on patient-to-patient ties among 200 patients obtained from PLM. We then characterized patients’ online social activities by measuring the numbers of “posts and views” and “helpful marks” each patient obtained. The patients’ recovery data were obtained from their self-reported status information that was also available on PLM. We found that some node properties (in-degree, eigenvector centrality and PageRank and the two online social activity measures were significantly correlated with patients’ recovery. Furthermore, we re-collected the patients’ recovery data two months after the first data collection. We found significant correlations between the patients’ social behaviors and the second recovery data, which were collected two months apart. Our results indicated that social interactions in online communities such as PLM were significantly associated with the current and future recoveries of patients with mental disorders.

  20. Adaptive online state-of-charge determination based on neuro-controller and neural network

    Energy Technology Data Exchange (ETDEWEB)

    Shen Yanqing, E-mail: network_hawk@126.co [Department of Automation, Chongqing Industry Polytechnic College, Jiulongpo District, Chongqing 400050 (China)

    2010-05-15

    This paper presents a novel approach using adaptive artificial neural network based model and neuro-controller for online cell State of Charge (SOC) determination. Taking cell SOC as model's predictive control input unit, radial basis function neural network, which can adjust its structure to prediction error with recursive least square algorithm, is used to simulate battery system. Besides that, neuro-controller based on Back-Propagation Neural Network (BPNN) and modified PID controller is used to decide the control input of battery system, i.e., cell SOC. Finally this algorithm is applied for the SOC determination of lead-acid batteries, and results of lab tests on physical cells, compared with model prediction, are presented. Results show that the ANN based battery system model adaptively simulates battery system with great accuracy, and the predicted SOC simultaneously converges to the real value quickly within the error of +-1 as time goes on.

  1. Exploring the Usefulness of Corporate Online Social Networks in the Human Resource Management

    Directory of Open Access Journals (Sweden)

    Slaviša Sovilj

    2014-04-01

    who represent the nodes of communication, but also provides a wealth of information on employees or those who are interested in the right jobs, who use social networks to post information about themselves. This paper explored the possibility of obtaining information relevant to the selection of internal human resources based on an analysis of corporate online social networks. Research methods are taken from the field of graph theory and social network analysis (SNA, whereas in addition to quantitative parameters of nodes also additional dimensions of data filtering are considered. This approach is called the extended SNA. In addition to demonstrating and explaining, the extended SNA has developed an application that simulates the communication between employees within a corporation, for the analysis and detection of suitable employees, and visualizes the results in the form of a graph.

  2. The Emergence of Contesting Motives for Student Feedback-Based Evaluation in Australian Higher Education

    Science.gov (United States)

    Darwin, Stephen

    2016-01-01

    Student feedback-based evaluation performs a significant social role in framing perceptions of the quality of teaching in contemporary Australian higher education. Yet its emergence is a relatively recent phenomenon, having only been in widespread application since the mid-1980s. The early manifestations of student feedback-based evaluation came…

  3. Using posts to an online social network to assess fishing effort

    Science.gov (United States)

    Martin, Dustin R.; Chizinski, Christopher J.; Eskridge, Kent M.; Pope, Kevin L

    2014-01-01

    Fisheries management has evolved from reservoir to watershed management, creating a need to simultaneously gather information within and across interacting reservoirs. However, costs to gather information on the fishing effort on multiple reservoirs using traditional creel methodology are often prohibitive. Angler posts about reservoirs online provide a unique medium to test hypotheses on the distribution of fishing pressure. We show that the activity on an online fishing social network is related to fishing effort and can be used to facilitate management goals. We searched the Nebraska Fish and Game Association Fishing Forum for all references from April 2009 to December 2010 to 19 reservoirs that comprise the Salt Valley regional fishery in southeastern Nebraska. The number of posts was positively related to monthly fishing effort on a regional scale, with individual reservoirs having the most annual posts also having the most annual fishing effort. Furthermore, this relationship held temporally. Online fishing social networks provide the potential to assess effort on larger spatial scales than currently feasible.

  4. Telecommunications Network Measurements of Online Gambling Behavior in Switzerland: A Feasibility Study.

    Science.gov (United States)

    Bitar, Raoul; Nordt, Carlos; Grosshans, Martin; Herdener, Marcus; Seifritz, Erich; Mutschler, Jochen

    2017-01-01

    Methodological shortcomings of gambling studies relying on self-report or on data sets derived from gambling operators tend to result in biased conclusions. The aim of this study was to analyze online gambling behavior using a novel network database approach. From October 13 to October 26, 2014, telecommunications network data from a major telecommunications provider in Switzerland were analyzed. Netflows between mobile devices and a poker operator were quantified to measure the gambling duration and session number. Time spent gambling during night and working hours was compared between devices with longest (red group), intermediate (orange group), and shortest gambling time (green group). Online gambling behavior differed depending on overall gambling time, F (2, 3,143). Night and working hours gambling was the highest in the red group (53%), compared to the orange (50.1%) and the green groups (41.5%). Post hoc analyses indicated significant differences between the orange and green groups (p social media use, and online pornography. © 2017 S. Karger AG, Basel.

  5. Indigenous development and networking of online radon monitors in the underground uranium mine

    International Nuclear Information System (INIS)

    Gaware, J.J.; Sahoo, B.K.; Sapra, B.K.; Mayya, Y.S.

    2011-01-01

    There has been a long standing demand for online monitoring of radon level in various locations of underground Uranium mine for taking care of radiological protection to workers. Nowadays, radon ( 222 Rn) monitors, based on electrostatic collection of charged progeny and subsequent detection by semiconductor detector are increasingly employed for radon monitoring in environment. However, such instruments have some limitations such as (i) requirement of additional dryer since sensitivity is dependent on the humidity (ii) cannot be connected to a network and (iii) not cost effective etc. Hence use of such instruments in underground uranium mine (humidity level >90), may not be reliable. Towards this end, we have indigenously developed radon monitor based on electrostatic collection and scintillation technology for the online monitoring in uranium mine. This instrument overcomes the above mentioned limitation of commercial radon monitors and based on custom made features. Different tests and measurements were carried out and compared with commercial instruments. It was found to be in an excellent agreement with the commercial instruments. A few such instruments have been installed in different locations of uranium mine at Turamdih and connected to a network system for online monitoring and display. (author)

  6. Non-linguistic learning and aphasia: Evidence from a paired associate and feedback-based task

    Science.gov (United States)

    Vallila-Rohter, Sofia; Kiran, Swathi

    2013-01-01

    Though aphasia is primarily characterized by impairments in the comprehension and/or expression of language, research has shown that patients with aphasia also show deficits in cognitive-linguistic domains such as attention, executive function, concept knowledge and memory (Helm-Estabrooks, 2002 for review). Research in aphasia suggests that cognitive impairments can impact the online construction of language, new verbal learning, and transactional success (Freedman & Martin, 2001; Hula & McNeil, 2008; Ramsberger, 2005). In our research, we extend this hypothesis to suggest that general cognitive deficits influence progress with therapy. The aim of our study is to explore learning, a cognitive process that is integral to relearning language, yet underexplored in the field of aphasia rehabilitation. We examine non-linguistic category learning in patients with aphasia (n=19) and in healthy controls (n=12), comparing feedback and non-feedback based instruction. Participants complete two computer-based learning tasks that require them to categorize novel animals based on the percentage of features shared with one of two prototypes. As hypothesized, healthy controls showed successful category learning following both methods of instruction. In contrast, only 60% of our patient population demonstrated successful non-linguistic category learning. Patient performance was not predictable by standardized measures of cognitive ability. Results suggest that general learning is affected in aphasia and is a unique, important factor to consider in the field of aphasia rehabilitation. PMID:23127795

  7. Friending, IMing, and hanging out face-to-face: overlap in adolescents' online and offline social networks.

    Science.gov (United States)

    Reich, Stephanie M; Subrahmanyam, Kaveri; Espinoza, Guadalupe

    2012-03-01

    Many new and important developmental issues are encountered during adolescence, which is also a time when Internet use becomes increasingly popular. Studies have shown that adolescents are using these online spaces to address developmental issues, especially needs for intimacy and connection to others. Online communication with its potential for interacting with unknown others, may put teens at increased risk. Two hundred and fifty-one high school students completed an in-person survey, and 126 of these completed an additional online questionnaire about how and why they use the Internet, their activities on social networking sites (e.g., Facebook, MySpace) and their reasons for participation, and how they perceive these online spaces to impact their friendships. To examine the extent of overlap between online and offline friends, participants were asked to list the names of their top interaction partners offline and online (Facebook and instant messaging). Results reveal that adolescents mainly use social networking sites to connect with others, in particular with people known from offline contexts. While adolescents report little monitoring by their parents, there was no evidence that teens are putting themselves at risk by interacting with unknown others. Instead, adolescents seem to use the Internet, especially social networking sites, to connect with known others. While the study found moderate overlap between teens' closest online and offline friends, the patterns suggest that adolescents use online contexts to strengthen offline relationships. PsycINFO Database Record (c) 2012 APA, all rights reserved.

  8. Enforcement of Privacy Policies over Multiple Online Social Networks for Collaborative Activities

    Science.gov (United States)

    Wu, Zhengping; Wang, Lifeng

    Our goal is to tend to develop an enforcement architecture of privacy policies over multiple online social networks. It is used to solve the problem of privacy protection when several social networks build permanent or temporary collaboration. Theoretically, this idea is practical, especially due to more and more social network tend to support open source framework “OpenSocial”. But as we known different social network websites may have the same privacy policy settings based on different enforcement mechanisms, this would cause problems. In this case, we have to manually write code for both sides to make the privacy policy settings enforceable. We can imagine that, this is a huge workload based on the huge number of current social networks. So we focus on proposing a middleware which is used to automatically generate privacy protection component for permanent integration or temporary interaction of social networks. This middleware provide functions, such as collecting of privacy policy of each participant in the new collaboration, generating a standard policy model for each participant and mapping all those standard policy to different enforcement mechanisms of those participants.

  9. Association between online social networking and depression in high school students: behavioral physiology viewpoint.

    Science.gov (United States)

    Pantic, Igor; Damjanovic, Aleksandar; Todorovic, Jovana; Topalovic, Dubravka; Bojovic-Jovic, Dragana; Ristic, Sinisa; Pantic, Senka

    2012-03-01

    Frequent use of Facebook and other social networks is thought to be associated with certain behavioral changes, and some authors have expressed concerns about its possible detrimental effect on mental health. In this work, we investigated the relationship between social networking and depression indicators in adolescent population. Total of 160 high school students were interviewed using an anonymous, structured questionnaire and Back Depression Inventory - second edition (BDI-II-II). Apart from BDI-II-II, students were asked to provide the data for height and weight, gender, average daily time spent on social networking sites, average time spent watching TV, and sleep duration in a 24-hour period. Average BDI-II-II score was 8.19 (SD=5.86). Average daily time spent on social networking was 1.86 h (SD=2.08 h), and average time spent watching TV was 2.44 h (SD=1.74 h). Average body mass index of participants was 21.84 (SD=3.55) and average sleep duration was 7.37 (SD=1.82). BDI-II-II score indicated minimal depression in 104 students, mild depression in 46 students, and moderate depression in 10 students. Statistically significant positive correlation (psocial networking. Our results indicate that online social networking is related to depression. Additional research is required to determine the possible causal nature of this relationship.

  10. Factors associated with online victimisation among Malaysian adolescents who use social networking sites: a cross-sectional study

    Science.gov (United States)

    Marret, Mary J; Choo, Wan Yuen

    2017-01-01

    Objective To determine the prevalence of online interpersonal victimisation and its association with patterns of social networking site (SNS) use, offline victimisation, offline perpetration and parental conflict among Malaysian adolescents using SNS. Methods A cross-sectional study of students from randomly selected public secondary schools in the state of Negeri Sembilan was conducted using an anonymous self-administered questionnaire. The questionnaire examined patterns of SNS use and included measures of online victimisation, online perpetration, offline victimisation and parental conflict. A response rate of 91% from a total of 1634 yielded a sample of 1487 students between 15 years and 16 years of age. Results Ninety-two per cent of respondents had used at least one SNS. More than half of SNS users (52.2%) reported experiences of online victimisation over the past 12 months. Boys were significantly more likely to experience online harassment compared with girls (52.2% vs 43.3%, p<0.001). There were no significant gender differences in experiences of unwanted sexual solicitation. Adolescents who engaged in perpetration behaviours online had almost six times higher odds of reporting frequent online victimisation compared with online behaviours involving personal disclosure. There was a significant dose-response relationship between engagement in multiple types of online behaviour and the risk of frequent online victimisation. Both online and offline perpetrations were associated with an increased risk of victimisation. Those who were victimised offline or experienced parental conflict were twice as likely to report online victimisation. Conclusion Interventions to prevent online electronic aggression should target perpetration behaviour both online and offline. Youth should be equipped with skills in communication and decision-making in relationships that can be applied across a spectrum of contexts both online and offline. PMID:28667209

  11. Context-specific protein network miner - an online system for exploring context-specific protein interaction networks from the literature

    KAUST Repository

    Chowdhary, Rajesh

    2012-04-06

    Background: Protein interaction networks (PINs) specific within a particular context contain crucial information regarding many cellular biological processes. For example, PINs may include information on the type and directionality of interaction (e.g. phosphorylation), location of interaction (i.e. tissues, cells), and related diseases. Currently, very few tools are capable of deriving context-specific PINs for conducting exploratory analysis. Results: We developed a literature-based online system, Context-specific Protein Network Miner (CPNM), which derives context-specific PINs in real-time from the PubMed database based on a set of user-input keywords and enhanced PubMed query system. CPNM reports enriched information on protein interactions (with type and directionality), their network topology with summary statistics (e.g. most densely connected proteins in the network; most densely connected protein-pairs; and proteins connected by most inbound/outbound links) that can be explored via a user-friendly interface. Some of the novel features of the CPNM system include PIN generation, ontology-based PubMed query enhancement, real-time, user-queried, up-to-date PubMed document processing, and prediction of PIN directionality. Conclusions: CPNM provides a tool for biologists to explore PINs. It is freely accessible at http://www.biotextminer.com/CPNM/. © 2012 Chowdhary et al.

  12. Context-specific protein network miner - an online system for exploring context-specific protein interaction networks from the literature

    KAUST Repository

    Chowdhary, Rajesh; Tan, Sin Lam; Zhang, Jinfeng; Karnik, Shreyas; Bajic, Vladimir B.; Liu, Jun S.

    2012-01-01

    Background: Protein interaction networks (PINs) specific within a particular context contain crucial information regarding many cellular biological processes. For example, PINs may include information on the type and directionality of interaction (e.g. phosphorylation), location of interaction (i.e. tissues, cells), and related diseases. Currently, very few tools are capable of deriving context-specific PINs for conducting exploratory analysis. Results: We developed a literature-based online system, Context-specific Protein Network Miner (CPNM), which derives context-specific PINs in real-time from the PubMed database based on a set of user-input keywords and enhanced PubMed query system. CPNM reports enriched information on protein interactions (with type and directionality), their network topology with summary statistics (e.g. most densely connected proteins in the network; most densely connected protein-pairs; and proteins connected by most inbound/outbound links) that can be explored via a user-friendly interface. Some of the novel features of the CPNM system include PIN generation, ontology-based PubMed query enhancement, real-time, user-queried, up-to-date PubMed document processing, and prediction of PIN directionality. Conclusions: CPNM provides a tool for biologists to explore PINs. It is freely accessible at http://www.biotextminer.com/CPNM/. © 2012 Chowdhary et al.

  13. Use of online social networking sites among pre-service information technology teachers

    Directory of Open Access Journals (Sweden)

    Elif Buğra Kuzu

    2013-12-01

    Full Text Available The current study aimed to investigate the current status and perceptions of pre-service information technology (IT teachers regarding the use of online social networking sites (SNSs. The investigation was further supported through participant feedback regarding the design and implementation of a blended learning environment to embrace online SNSs in instructional settings. The study had a qualitative nature and employed a focus group interview to collect data. Participants were ten fourth graders who were randomly selected from voluntary undergraduate students enrolled at an IT education department of a Turkish state university. Researchers resorted to content analysis through an inductive coding process, provided themes addressing student perceptions and needs, and proposed implications and suggestions for further instructional practices.

  14. An Ensemble of Neural Networks for Online Electron Filtering at the ATLAS Experiment.

    CERN Document Server

    Da Fonseca Pinto, Joao Victor; The ATLAS collaboration

    2018-01-01

    In 2017 the ATLAS experiment implemented an ensemble of neural networks (NeuralRinger algorithm) dedicated to improving the performance of filtering events containing electrons in the high-input rate online environment of the Large Hadron Collider at CERN, Geneva. The ensemble employs a concept of calorimetry rings. The training procedure and final structure of the ensemble are used to minimize fluctuations from detector response, according to the particle energy and position of incidence. A detailed study was carried out to assess profile distortions in crucial offline quantities through the usage of statistical tests and residual analysis. These details and the online performance of this algorithm during the 2017 data-taking will be presented.

  15. On-Line Tracking Controller for Brushless DC Motor Drives Using Artificial Neural Networks

    Science.gov (United States)

    Rubaai, Ahmed

    1996-01-01

    A real-time control architecture is developed for time-varying nonlinear brushless dc motors operating in a high performance drives environment. The developed control architecture possesses the capabilities of simultaneous on-line identification and control. The dynamics of the motor are modeled on-line and controlled using an artificial neural network, as the system runs. The control architecture combines the experience and dependability of adaptive tracking systems with potential and promise of the neural computing technology. The sensitivity of real-time controller to parametric changes that occur during training is investigated. Such changes are usually manifested by rapid changes in the load of the brushless motor drives. This sudden change in the external load is simulated for the sigmoidal and sinusoidal reference tracks. The ability of the neuro-controller to maintain reasonable tracking accuracy in the presence of external noise is also verified for a number of desired reference trajectories.

  16. An Analysis of Density and Degree-Centrality According to the Social Networking Structure Formed in an Online Learning Environment

    Science.gov (United States)

    Ergün, Esin; Usluel, Yasemin Koçak

    2016-01-01

    In this study, we assessed the communication structure in an educational online learning environment using social network analysis (SNA). The communication structure was examined with respect to time, and instructor's participation. The course was implemented using ELGG, a network learning environment, blended with face-to-face sessions over a…

  17. The Role of online Social networks in Teaching and Learning a foreign Language : Effects on Learning Process and Outcome

    NARCIS (Netherlands)

    Akbari, E.

    2016-01-01

    Today, online social networks are among the most important communications tools, connecting millions of people with common interests and ideas all over the world (Zaidieh, 2012). The rapid proliferation of Internet services has facilitated access to these networks not only via computers, but also

  18. Long Short-Term Memory Neural Networks for Online Disturbance Detection in Satellite Image Time Series

    Directory of Open Access Journals (Sweden)

    Yun-Long Kong

    2018-03-01

    Full Text Available A satellite image time series (SITS contains a significant amount of temporal information. By analysing this type of data, the pattern of the changes in the object of concern can be explored. The natural change in the Earth’s surface is relatively slow and exhibits a pronounced pattern. Some natural events (for example, fires, floods, plant diseases, and insect pests and human activities (for example, deforestation and urbanisation will disturb this pattern and cause a relatively profound change on the Earth’s surface. These events are usually referred to as disturbances. However, disturbances in ecosystems are not easy to detect from SITS data, because SITS contain combined information on disturbances, phenological variations and noise in remote sensing data. In this paper, a novel framework is proposed for online disturbance detection from SITS. The framework is based on long short-term memory (LSTM networks. First, LSTM networks are trained by historical SITS. The trained LSTM networks are then used to predict new time series data. Last, the predicted data are compared with real data, and the noticeable deviations reveal disturbances. Experimental results using 16-day compositions of the moderate resolution imaging spectroradiometer (MOD13Q1 illustrate the effectiveness and stability of the proposed approach for online disturbance detection.

  19. From Subjective Trust to Objective Trustworthiness in On-line Social Networks: Overview and Challenges

    Directory of Open Access Journals (Sweden)

    David Zejda

    2010-04-01

    Full Text Available Nowadays dozens of people share their content in the current Web 2.0 space, talk with friends in social networking sites such as Facebook and live on the Net in many other ways. They do all this quite naturally, forgetting the healthy cautiousness sometimes. In real life we rely on trusted people. Do we know how to reflect real-world trust mechanisms into on-line social software? In the article we focused to bring overview on state of the art in main ideas behind a trust processing in online social networking systems. What are common sources of subjective trust, how the trust emerges and what are the sources of trust dynamics? How can be trust captured into the systems, how can be explicit trust processed to infer indirect trust, the trust between users who do not know each other? And what are the ways to infer objective metrics of trust, the reputation or trustworthiness? Finally, we point out selected challenges related to the trust in current highly dynamic social networks.

  20. An online database for informing ecological network models: http://kelpforest.ucsc.edu.

    Science.gov (United States)

    Beas-Luna, Rodrigo; Novak, Mark; Carr, Mark H; Tinker, Martin T; Black, August; Caselle, Jennifer E; Hoban, Michael; Malone, Dan; Iles, Alison

    2014-01-01

    Ecological network models and analyses are recognized as valuable tools for understanding the dynamics and resiliency of ecosystems, and for informing ecosystem-based approaches to management. However, few databases exist that can provide the life history, demographic and species interaction information necessary to parameterize ecological network models. Faced with the difficulty of synthesizing the information required to construct models for kelp forest ecosystems along the West Coast of North America, we developed an online database (http://kelpforest.ucsc.edu/) to facilitate the collation and dissemination of such information. Many of the database's attributes are novel yet the structure is applicable and adaptable to other ecosystem modeling efforts. Information for each taxonomic unit includes stage-specific life history, demography, and body-size allometries. Species interactions include trophic, competitive, facilitative, and parasitic forms. Each data entry is temporally and spatially explicit. The online data entry interface allows researchers anywhere to contribute and access information. Quality control is facilitated by attributing each entry to unique contributor identities and source citations. The database has proven useful as an archive of species and ecosystem-specific information in the development of several ecological network models, for informing management actions, and for education purposes (e.g., undergraduate and graduate training). To facilitate adaptation of the database by other researches for other ecosystems, the code and technical details on how to customize this database and apply it to other ecosystems are freely available and located at the following link (https://github.com/kelpforest-cameo/databaseui).

  1. Sharing data for public health research by members of an international online diabetes social network.

    Directory of Open Access Journals (Sweden)

    Elissa R Weitzman

    2011-04-01

    Full Text Available Surveillance and response to diabetes may be accelerated through engaging online diabetes social networks (SNs in consented research. We tested the willingness of an online diabetes community to share data for public health research by providing members with a privacy-preserving social networking software application for rapid temporal-geographic surveillance of glycemic control.SN-mediated collection of cross-sectional, member-reported data from an international online diabetes SN entered into a software application we made available in a "Facebook-like" environment to enable reporting, charting and optional sharing of recent hemoglobin A1c values through a geographic display. Self-enrollment by 17% (n = 1,136 of n = 6,500 active members representing 32 countries and 50 US states. Data were current with 83.1% of most recent A1c values reported obtained within the past 90 days. Sharing was high with 81.4% of users permitting data donation to the community display. 34.1% of users also displayed their A1cs on their SN profile page. Users selecting the most permissive sharing options had a lower average A1c (6.8% than users not sharing with the community (7.1%, p = .038. 95% of users permitted re-contact. Unadjusted aggregate A1c reported by US users closely resembled aggregate 2007-2008 NHANES estimates (respectively, 6.9% and 6.9%, p = 0.85.Success within an early adopter community demonstrates that online SNs may comprise efficient platforms for bidirectional communication with and data acquisition from disease populations. Advancing this model for cohort and translational science and for use as a complementary surveillance approach will require understanding of inherent selection and publication (sharing biases in the data and a technology model that supports autonomy, anonymity and privacy.

  2. Sharing data for public health research by members of an international online diabetes social network.

    Science.gov (United States)

    Weitzman, Elissa R; Adida, Ben; Kelemen, Skyler; Mandl, Kenneth D

    2011-04-27

    Surveillance and response to diabetes may be accelerated through engaging online diabetes social networks (SNs) in consented research. We tested the willingness of an online diabetes community to share data for public health research by providing members with a privacy-preserving social networking software application for rapid temporal-geographic surveillance of glycemic control. SN-mediated collection of cross-sectional, member-reported data from an international online diabetes SN entered into a software application we made available in a "Facebook-like" environment to enable reporting, charting and optional sharing of recent hemoglobin A1c values through a geographic display. Self-enrollment by 17% (n = 1,136) of n = 6,500 active members representing 32 countries and 50 US states. Data were current with 83.1% of most recent A1c values reported obtained within the past 90 days. Sharing was high with 81.4% of users permitting data donation to the community display. 34.1% of users also displayed their A1cs on their SN profile page. Users selecting the most permissive sharing options had a lower average A1c (6.8%) than users not sharing with the community (7.1%, p = .038). 95% of users permitted re-contact. Unadjusted aggregate A1c reported by US users closely resembled aggregate 2007-2008 NHANES estimates (respectively, 6.9% and 6.9%, p = 0.85). Success within an early adopter community demonstrates that online SNs may comprise efficient platforms for bidirectional communication with and data acquisition from disease populations. Advancing this model for cohort and translational science and for use as a complementary surveillance approach will require understanding of inherent selection and publication (sharing) biases in the data and a technology model that supports autonomy, anonymity and privacy.

  3. Social Network Analysis of Elders' Health Literacy and their Use of Online Health Information.

    Science.gov (United States)

    Jang, Haeran; An, Ji-Young

    2014-07-01

    Utilizing social network analysis, this study aimed to analyze the main keywords in the literature regarding the health literacy of and the use of online health information by aged persons over 65. Medical Subject Heading keywords were extracted from articles on the PubMed database of the National Library of Medicine. For health literacy, 110 articles out of 361 were initially extracted. Seventy-one keywords out of 1,021 were finally selected after removing repeated keywords and applying pruning. Regarding the use of online health information, 19 articles out of 26 were selected. One hundred forty-four keywords were initially extracted. After removing the repeated keywords, 74 keywords were finally selected. Health literacy was found to be strongly connected with 'Health knowledge, attitudes, practices' and 'Patient education as topic.' 'Computer literacy' had strong connections with 'Internet' and 'Attitude towards computers.' 'Computer literacy' was connected to 'Health literacy,' and was studied according to the parameters 'Attitude towards health' and 'Patient education as topic.' The use of online health information was strongly connected with 'Health knowledge, attitudes, practices,' 'Consumer health information,' 'Patient education as topic,' etc. In the network, 'Computer literacy' was connected with 'Health education,' 'Patient satisfaction,' 'Self-efficacy,' 'Attitude to computer,' etc. Research on older citizens' health literacy and their use of online health information was conducted together with study of computer literacy, patient education, attitude towards health, health education, patient satisfaction, etc. In particular, self-efficacy was noted as an important keyword. Further research should be conducted to identify the effective outcomes of self-efficacy in the area of interest.

  4. Using the Internet, Online Social Networks and Potentially Incurred Risk: Student Opinions

    Directory of Open Access Journals (Sweden)

    Gintautė Žibėnienė

    2013-08-01

    Full Text Available Regulation of harmful content on the Internet is a soaring problem in the expansion of the information society, and it is being discussed in different European countries. Therefore, it is important to discuss the issue of being safe online: to do research on what children think about when using the Internet, threats experienced while online, to discuss ways of recognising and protecting children from online threats (such as cyber bullying, bullying, abuse, temptations with purpose of sexual harassment, leaking of personal information, spreading, harmful and illegal Internet content, etc.. The research objective of this paper is to present the opinion of gymnasium students on using the Internet, online social networks and likely experienced threats. The methodology—opinion research of the gymnasium students, which was carried out 17–21 December 2012; an analysis of professional target publications and a questionnaire survey were also applied. Analysis of the research findings was based on the analysis methods of quantity analysis (descriptive and analysis of quality content. Statistical findings were analysed applying the software “Statistical Package for the Social Sciences (SPSS 21.0 for Windows.” According to the research of student opinion, it was revealed that the most common student online activities are browsing of chat websites, exchange of videos and other material, viewing, listening and participating in social networks, whereas erotica and viewing of pornography are the rarest activities and are unimportant for students. Online social networks are especially popular among students, as most interviewed students (95.3% have their own profile in social networks. Students mostly visit social networks to communicate, to make friends (77.1% of respondents, however, every second student (60.7% visits them just to spend time, which can be assumed about the problems of students’ leisure time. The vast majority of students think that

  5. Social network analysis as a method for analyzing interaction in collaborative online learning environments

    Directory of Open Access Journals (Sweden)

    Patricia Rice Doran

    2011-12-01

    Full Text Available Social network analysis software such as NodeXL has been used to describe participation and interaction in numerous social networks, but it has not yet been widely used to examine dynamics in online classes, where participation is frequently required rather than optional and participation patterns may be impacted by the requirements of the class, the instructor’s activities, or participants’ intrinsic engagement with the subject matter. Such social network analysis, which examines the dynamics and interactions among groups of participants in a social network or learning group, can be valuable in programs focused on teaching collaborative and communicative skills, including teacher preparation programs. Applied to these programs, social network analysis can provide information about instructional practices likely to facilitate student interaction and collaboration across diverse student populations. This exploratory study used NodeXL to visualize students’ participation in an online course, with the goal of identifying (1 ways in which NodeXL could be used to describe patterns in participant interaction within an instructional setting and (2 identifying specific patterns in participant interaction among students in this particular course. In this sample, general education teachers demonstrated higher measures of connection and interaction with other participants than did those from specialist (ESOL or special education backgrounds, and tended to interact more frequently with all participants than the majority of participants from specialist backgrounds. We recommend further research to delineate specific applications of NodeXL within an instructional context, particularly to identify potential patterns in student participation based on variables such as gender, background, cultural and linguistic heritage, prior training and education, and prior experience so that instructors can ensure their practice helps to facilitate student interaction

  6. How Irish Political Parties are Using Social Networking Sites to Reach Generation Z: an Insight into a New Online Social Network in a Small Democracy

    OpenAIRE

    Lynch, Kevin; Hogan, John

    2016-01-01

    This study, using in-depth interviews and focus groups, examines perceptions of social networking sites as a means of communicating with Generation Z, from the perspectives of the major Irish political parties using these online resources and the perspective of their young target audience. There are two research questions: (1) How do political parties perceive social networking sites’ role in communicating with Generation Z? and (2) How do members of Generation Z perceive social networking si...

  7. Effects of Social Network Exposure on Nutritional Learning: Development of an Online Educational Platform.

    Science.gov (United States)

    Dagan, Noa; Beskin, Daniel; Brezis, Mayer; Reis, Ben Y

    2015-10-05

    Social networking sites (SNSs) such as Facebook have the potential to enhance online public health interventions, in part, as they provide social exposure and reinforcement. The objective of the study was to evaluate whether social exposure provided by SNSs enhances the effects of online public health interventions. As a sample intervention, we developed Food Hero, an online platform for nutritional education in which players feed a virtual character according to their own nutritional needs and complete a set of virtual sport challenges. The platform was developed in 2 versions: a "private version" in which a user can see only his or her own score, and a "social version" in which a user can see other players' scores, including preexisting Facebook friends. We assessed changes in participants' nutritional knowledge using 4 quiz scores and 3 menu-assembly scores. Monitoring feeding and exercising attempts assessed engagement with the platform. The 2 versions of the platform were randomly assigned between a study group (30 members receiving the social version) and a control group (33 members, private version). The study group's performance on the quizzes gradually increased over time, relative to that of the control group, becoming significantly higher by the fourth quiz (P=.02). Furthermore, the study group's menu-assembly scores improved over time compared to the first score, whereas the control group's performance deteriorated. Study group members spent an average of 3:40 minutes assembling each menu compared to 2:50 minutes in the control group, and performed an average of 1.58 daily sport challenges, compared to 1.21 in the control group (P=.03). This work focused on isolating the SNSs' social effects in order to help guide future online interventions. Our results indicate that the social exposure provided by SNSs is associated with increased engagement and learning in an online nutritional educational platform.

  8. Active Probing Feedback based Self Configurable Intelligent Distributed Antenna System

    DEFF Research Database (Denmark)

    Kumar, Ambuj

    collectively as Place Time Coverage & Capacity (PTC2). The dissertation proves through the concept of the PTC2 that the network performance can severely be degraded by the excessive and unrealistic site demands, the network management inefficiency, and the consequence of the accumulation of subscribers...... challenge through a viable solution that is based on injecting intelligence and services in parallel layers through a Distributed Antenna Systems (DAS) network. This approach would enable the remote sites to acquire intelligence and a resource pool at the same time, thereby managing the network dynamics...... promptly and aptly to absorb the PTC2 wobble. An Active Probing Management System (APMS) is proposed as a supporting architecture, to assist the intelligent system to keep a check on the variations at each and every site by either deploying the additional antenna or by utilising the service antenna...

  9. Factors associated with online victimisation among Malaysian adolescents who use social networking sites: a cross-sectional study.

    Science.gov (United States)

    Marret, Mary J; Choo, Wan Yuen

    2017-06-30

    To determine the prevalence of online interpersonal victimisation and its association with patterns of social networking site (SNS) use, offline victimisation, offline perpetration and parental conflict among Malaysian adolescents using SNS. A cross-sectional study of students from randomly selected public secondary schools in the state of Negeri Sembilan was conducted using an anonymous self-administered questionnaire. The questionnaire examined patterns of SNS use and included measures of online victimisation, online perpetration, offline victimisation and parental conflict. A response rate of 91% from a total of 1634 yielded a sample of 1487 students between 15 years and 16 years of age. Ninety-two per cent of respondents had used at least one SNS. More than half of SNS users (52.2%) reported experiences of online victimisation over the past 12 months. Boys were significantly more likely to experience online harassment compared with girls (52.2% vs 43.3%, ponline had almost six times higher odds of reporting frequent online victimisation compared with online behaviours involving personal disclosure. There was a significant dose-response relationship between engagement in multiple types of online behaviour and the risk of frequent online victimisation. Both online and offline perpetrations were associated with an increased risk of victimisation. Those who were victimised offline or experienced parental conflict were twice as likely to report online victimisation. Interventions to prevent online electronic aggression should target perpetration behaviour both online and offline. Youth should be equipped with skills in communication and decision-making in relationships that can be applied across a spectrum of contexts both online and offline. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  10. Online social networks for crowdsourced multimedia-involved behavioral testing: An empirical study

    Directory of Open Access Journals (Sweden)

    Jun-Ho eChoi

    2016-01-01

    Full Text Available Online social networks have emerged as effective crowdsourcing media to recruit participants in recent days. However, issues regarding how to effectively exploit them have not been adequately addressed yet. In this paper, we investigate the reliability and effectiveness of multimedia-involved behavioral testing via social network-based crowdsourcing, especially focused on Facebook as a medium to recruit participants. We conduct a crowdsourcing-based experiment for a music recommendation problem. It is shown that different advertisement methods yield different degrees of efficiency and there exist significant differences in behavioral patterns across different genders and different age groups. In addition, we perform a comparison of our experiment with other multimedia-involved crowdsourcing experiments built on Amazon Mechanical Turk (MTurk, which suggests that crowdsourcing-based experiments using social networks for recruitment can achieve comparable efficiency. Based on the analysis results, advantages and disadvantages of social network-based crowdsourcing and suggestions for successful experiments are also discussed. We conclude that social networks have the potential to support multimedia-involved behavioral tests to gather in-depth data even for long-term periods.

  11. Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

    Science.gov (United States)

    Williams-Hayes, Peggy S.

    2004-01-01

    The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

  12. Online Social Networks for Crowdsourced Multimedia-Involved Behavioral Testing: An Empirical Study

    Science.gov (United States)

    Choi, Jun-Ho; Lee, Jong-Seok

    2016-01-01

    Online social networks have emerged as effective crowdsourcing media to recruit participants in recent days. However, issues regarding how to effectively exploit them have not been adequately addressed yet. In this paper, we investigate the reliability and effectiveness of multimedia-involved behavioral testing via social network-based crowdsourcing, especially focused on Facebook as a medium to recruit participants. We conduct a crowdsourcing-based experiment for a music recommendation problem. It is shown that different advertisement methods yield different degrees of efficiency and there exist significant differences in behavioral patterns across different genders and different age groups. In addition, we perform a comparison of our experiment with other multimedia-involved crowdsourcing experiments built on Amazon Mechanical Turk (MTurk), which suggests that crowdsourcing-based experiments using social networks for recruitment can achieve comparable efficiency. Based on the analysis results, advantages and disadvantages of social network-based crowdsourcing and suggestions for successful experiments are also discussed. We conclude that social networks have the potential to support multimedia-involved behavioral tests to gather in-depth data even for long-term periods. PMID:26793137

  13. Online Social Networks for Crowdsourced Multimedia-Involved Behavioral Testing: An Empirical Study.

    Science.gov (United States)

    Choi, Jun-Ho; Lee, Jong-Seok

    2015-01-01

    Online social networks have emerged as effective crowdsourcing media to recruit participants in recent days. However, issues regarding how to effectively exploit them have not been adequately addressed yet. In this paper, we investigate the reliability and effectiveness of multimedia-involved behavioral testing via social network-based crowdsourcing, especially focused on Facebook as a medium to recruit participants. We conduct a crowdsourcing-based experiment for a music recommendation problem. It is shown that different advertisement methods yield different degrees of efficiency and there exist significant differences in behavioral patterns across different genders and different age groups. In addition, we perform a comparison of our experiment with other multimedia-involved crowdsourcing experiments built on Amazon Mechanical Turk (MTurk), which suggests that crowdsourcing-based experiments using social networks for recruitment can achieve comparable efficiency. Based on the analysis results, advantages and disadvantages of social network-based crowdsourcing and suggestions for successful experiments are also discussed. We conclude that social networks have the potential to support multimedia-involved behavioral tests to gather in-depth data even for long-term periods.

  14. Extraction of temporal networks from term co-occurrences in online textual sources.

    Directory of Open Access Journals (Sweden)

    Marko Popović

    Full Text Available A stream of unstructured news can be a valuable source of hidden relations between different entities, such as financial institutions, countries, or persons. We present an approach to continuously collect online news, recognize relevant entities in them, and extract time-varying networks. The nodes of the network are the entities, and the links are their co-occurrences. We present a method to estimate the significance of co-occurrences, and a benchmark model against which their robustness is evaluated. The approach is applied to a large set of financial news, collected over a period of two years. The entities we consider are 50 countries which issue sovereign bonds, and which are insured by Credit Default Swaps (CDS in turn. We compare the country co-occurrence networks to the CDS networks constructed from the correlations between the CDS. The results show relatively small, but significant overlap between the networks extracted from the news and those from the CDS correlations.

  15. An Introduction to Models of Online Peer-to-Peer Social Networking

    CERN Document Server

    Kesidis, George

    2010-01-01

    This book concerns peer-to-peer applications and mechanisms operating on the Internet, particularly those that are not fully automated and involve significant human interaction. So, the realm of interest is the intersection of distributed systems and online social networking. Generally, simple models are described to clarify the ideas. Beginning with short overviews of caching, graph theory and game theory, we cover the basic ideas of structured and unstructured search. We then describe a simple framework for reputations and for iterated referrals and consensus. This framework is applied to a

  16. Breach of Personal Security through Applicative use of Online Social Networks

    Directory of Open Access Journals (Sweden)

    Bojan Nikolovski

    2013-11-01

    Full Text Available Throughout this article there is an attempt to indicate the threats of potential to breach of personal security through applicative use of internet as well as applicative use of online social networks. In addition to many other ways of privacy protection applicative users of social network’s sites must take into considerations the risk of distributing private data. Through a series of actions and settings users can customize the security settings with the ultimate goal of reducing the risk of attack on their privacy.

  17. Online Particle Detection by Neural Networks Based on Topologic Calorimetry Information

    CERN Document Server

    Ciodaro, T; The ATLAS collaboration; Damazio, D; de Seixas, JM

    2011-01-01

    This paper presents the last results from the Ringer algorithm, which is based on artificial neural networks for the electron identification at the online filtering system of the ATLAS particle detector, in the context of the LHC experiment at CERN. The algorithm performs topological feature extraction over the ATLAS calorimetry information (energy measurements). Later, the extracted information is presented to a neural network classifier. Studies showed that the Ringer algorithm achieves high detection efficiency, while keeping the false alarm rate low. Optimizations, guided by detailed analysis, reduced the algorithm execution time in 59%. Also, the payload necessary to store the Ringer algorithm information represents less than 6.2 percent of the total filtering system amount

  18. Greek Civil Society’s Online Alternative Networks as Emergent Resilience Strategies in Time of Crisis

    Directory of Open Access Journals (Sweden)

    Maria Zafiropoulou

    2016-12-01

    Full Text Available The use of new communications technologies and social media, in Greece, during the time of crisis, has led to the development of numerous online informal Civil Society Networks (CSNs (i.e. networking-building platforms, self - organized groups in Facebook, forums, exchange platforms proposing a rethinking of the status quo of formal civil organizations. This research, utilizing the methodology of discourse analysis, aims at summarizing the rise of these networks in Greece that incorporates both solidarity initiatives and autonomous political/economic spaces and identify the indicative predictive factors of their survival and growth. Some basic conclusions that have been drawn through this research is that alternative online networks can be proven as indicative sign of the social dynamism of a given period but in order to be resilient and sustainable they should develop focal points of physical reference, pursue national representation, focus mainly on monothematic goods/services and cultivate, in several cases, links with relevant social movements and local or national NGOs. A general induction through this research is that a CSN, during this current crisis, stands between two classical models of reference in a society seeking modernity and flexibility and can be considered as a proposed type of effective experimentation and mobilization that can pursue common social goals and serve needs of deprived people. Some issues that still remain underexplored and need further elaboration are social and political identity of participants, the potential links with local, national and international communities, the functional balance between structure and flexibility as well as the efficient distribution of energy between solidarity and protest.

  19. [Semantic Network Analysis of Online News and Social Media Text Related to Comprehensive Nursing Care Service].

    Science.gov (United States)

    Kim, Minji; Choi, Mona; Youm, Yoosik

    2017-12-01

    As comprehensive nursing care service has gradually expanded, it has become necessary to explore the various opinions about it. The purpose of this study is to explore the large amount of text data regarding comprehensive nursing care service extracted from online news and social media by applying a semantic network analysis. The web pages of the Korean Nurses Association (KNA) News, major daily newspapers, and Twitter were crawled by searching the keyword 'comprehensive nursing care service' using Python. A morphological analysis was performed using KoNLPy. Nodes on a 'comprehensive nursing care service' cluster were selected, and frequency, edge weight, and degree centrality were calculated and visualized with Gephi for the semantic network. A total of 536 news pages and 464 tweets were analyzed. In the KNA News and major daily newspapers, 'nursing workforce' and 'nursing service' were highly rated in frequency, edge weight, and degree centrality. On Twitter, the most frequent nodes were 'National Health Insurance Service' and 'comprehensive nursing care service hospital.' The nodes with the highest edge weight were 'national health insurance,' 'wards without caregiver presence,' and 'caregiving costs.' 'National Health Insurance Service' was highest in degree centrality. This study provides an example of how to use atypical big data for a nursing issue through semantic network analysis to explore diverse perspectives surrounding the nursing community through various media sources. Applying semantic network analysis to online big data to gather information regarding various nursing issues would help to explore opinions for formulating and implementing nursing policies. © 2017 Korean Society of Nursing Science

  20. Imbalanced functional link between executive control network and reward network explain the online-game seeking behaviors in Internet gaming disorder.

    Science.gov (United States)

    Dong, Guangheng; Lin, Xiao; Hu, Yanbo; Xie, Chunming; Du, Xiaoxia

    2015-03-17

    Literatures have shown that Internet gaming disorder (IGD) subjects show impaired executive control and enhanced reward sensitivities than healthy controls. However, how these two networks jointly affect the valuation process and drive IGD subjects' online-game-seeking behaviors remains unknown. Thirty-five IGD and 36 healthy controls underwent a resting-states scan in the MRI scanner. Functional connectivity (FC) was examined within control and reward network seeds regions, respectively. Nucleus accumbens (NAcc) was selected as the node to find the interactions between these two networks. IGD subjects show decreased FC in the executive control network and increased FC in the reward network when comparing with the healthy controls. When examining the correlations between the NAcc and the executive control/reward networks, the link between the NAcc - executive control network is negatively related with the link between NAcc - reward network. The changes (decrease/increase) in IGD subjects' brain synchrony in control/reward networks suggest the inefficient/overly processing within neural circuitry underlying these processes. The inverse proportion between control network and reward network in IGD suggest that impairments in executive control lead to inefficient inhibition of enhanced cravings to excessive online game playing. This might shed light on the mechanistic understanding of IGD.

  1. Research on Linear Wireless Sensor Networks Used for Online Monitoring of Rolling Bearing in Freight Train

    International Nuclear Information System (INIS)

    Wang Nan; Meng Qingfeng; Zheng Bin; Li Tong; Ma Qinghai

    2011-01-01

    This paper presents a Wireless Sensor Networks (WSNs) technique for the purpose of on-line monitoring of rolling bearing in freight train. A new technical scheme including the arrangements of sensors, the design of sensor nodes and base station, routing protocols, signal acquirement, processing and transmission is described, and an on-line monitoring system is established. Considering the approximately linear arrangements of cars and the running state of freight train, a linear topology structure of WSNs is adopted and five linear routing protocols are discussed in detail as to obtain the desired minimum energy consumption of WSNs. By analysing the simulation results, an optimal multi-hop routing protocol named sub-section routing protocol according to equal distance is adopted, in which all sensor nodes are divided into different groups according to the equal transmission distance, the optimal transmission distance and number of hops of routing protocol are also studied. We know that the communication consumes significant power in WSNs, so, in order to save the limit power supply of WSNs, the data compression and coding scheme based on lifting integer wavelet and embedded zerotree wavelet (EZW) algorithms is studied to reduce the amounts of data transmitted. The experimental results of rolling bearing have been given at last to verify the effectiveness of data compression algorithm. The on-line monitoring system of rolling bearing in freight train will be applied to actual application in the near future.

  2. Muslim Young People Online: “Acts of Citizenship” in Socially Networked Spaces

    Directory of Open Access Journals (Sweden)

    Amelia Johns

    2014-08-01

    Full Text Available This paper reviews the current literature regarding Muslim young people’s online social networking and participatory practices with the aim of examining whether these practices open up new spaces of civic engagement and political participation. The paper focuses on the experiences of young Muslims living in western societies, where, since September 11, the ability to assert claims as citizens in the public arena has diminished. The paper draws upon Isin & Nielsen’s (2008 “acts of citizenship” to define the online practices of many Muslim youth, for whom the internet provides a space where new performances of citizenship are enacted outside of formal citizenship rights and spaces of participation. These “acts" are evaluated in light of theories which articulate the changing nature of publics and the public sphere in a digital era. The paper will use this conceptual framework in conjunction with the literature review to explore whether virtual, online spaces offer young Muslims an opportunity to create a more inclusive discursive space to interact with co-citizens, engage with social and political issues and assert their citizen rights than is otherwise afforded by formal political structures; a need highlighted by policies which target minority Muslim young people for greater civic participation but which do not reflect the interests and values of Muslim young people.

  3. Research on Linear Wireless Sensor Networks Used for Online Monitoring of Rolling Bearing in Freight Train

    Energy Technology Data Exchange (ETDEWEB)

    Wang Nan; Meng Qingfeng; Zheng Bin [Theory of Lubrication and Bearing Institute, Xi' an Jiaotong University Xi' an, 710049 (China); Li Tong; Ma Qinghai, E-mail: heroyoyu.2009@stu.xjtu.edu.cn [Xi' an Rail Bureau, Xi' an, 710054 (China)

    2011-07-19

    This paper presents a Wireless Sensor Networks (WSNs) technique for the purpose of on-line monitoring of rolling bearing in freight train. A new technical scheme including the arrangements of sensors, the design of sensor nodes and base station, routing protocols, signal acquirement, processing and transmission is described, and an on-line monitoring system is established. Considering the approximately linear arrangements of cars and the running state of freight train, a linear topology structure of WSNs is adopted and five linear routing protocols are discussed in detail as to obtain the desired minimum energy consumption of WSNs. By analysing the simulation results, an optimal multi-hop routing protocol named sub-section routing protocol according to equal distance is adopted, in which all sensor nodes are divided into different groups according to the equal transmission distance, the optimal transmission distance and number of hops of routing protocol are also studied. We know that the communication consumes significant power in WSNs, so, in order to save the limit power supply of WSNs, the data compression and coding scheme based on lifting integer wavelet and embedded zerotree wavelet (EZW) algorithms is studied to reduce the amounts of data transmitted. The experimental results of rolling bearing have been given at last to verify the effectiveness of data compression algorithm. The on-line monitoring system of rolling bearing in freight train will be applied to actual application in the near future.

  4. Social and place-focused communities in location-based online social networks

    Science.gov (United States)

    Brown, Chloë; Nicosia, Vincenzo; Scellato, Salvatore; Noulas, Anastasios; Mascolo, Cecilia

    2013-06-01

    Thanks to widely available, cheap Internet access and the ubiquity of smartphones, millions of people around the world now use online location-based social networking services. Understanding the structural properties of these systems and their dependence upon users' habits and mobility has many potential applications, including resource recommendation and link prediction. Here, we construct and characterise social and place-focused graphs by using longitudinal information about declared social relationships and about users' visits to physical places collected from a popular online location-based social service. We show that although the social and place-focused graphs are constructed from the same data set, they have quite different structural properties. We find that the social and location-focused graphs have different global and meso-scale structure, and in particular that social and place-focused communities have negligible overlap. Consequently, group inference based on community detection performed on the social graph alone fails to isolate place-focused groups, even though these do exist in the network. By studying the evolution of tie structure within communities, we show that the time period over which location data are aggregated has a substantial impact on the stability of place-focused communities, and that information about place-based groups may be more useful for user-centric applications than that obtained from the analysis of social communities alone.

  5. Identification of influential spreaders in online social networks using interaction weighted K-core decomposition method

    Science.gov (United States)

    Al-garadi, Mohammed Ali; Varathan, Kasturi Dewi; Ravana, Sri Devi

    2017-02-01

    Online social networks (OSNs) have become a vital part of everyday living. OSNs provide researchers and scientists with unique prospects to comprehend individuals on a scale and to analyze human behavioral patterns. Influential spreaders identification is an important subject in understanding the dynamics of information diffusion in OSNs. Targeting these influential spreaders is significant in planning the techniques for accelerating the propagation of information that is useful for various applications, such as viral marketing applications or blocking the diffusion of annoying information (spreading of viruses, rumors, online negative behaviors, and cyberbullying). Existing K-core decomposition methods consider links equally when calculating the influential spreaders for unweighted networks. Alternatively, the proposed link weights are based only on the degree of nodes. Thus, if a node is linked to high-degree nodes, then this node will receive high weight and is treated as an important node. Conversely, the degree of nodes in OSN context does not always provide accurate influence of users. In the present study, we improve the K-core method for OSNs by proposing a novel link-weighting method based on the interaction among users. The proposed method is based on the observation that the interaction of users is a significant factor in quantifying the spreading capability of user in OSNs. The tracking of diffusion links in the real spreading dynamics of information verifies the effectiveness of our proposed method for identifying influential spreaders in OSNs as compared with degree centrality, PageRank, and original K-core.

  6. Ethical considerations when employing fake identities in online social networks for research.

    Science.gov (United States)

    Elovici, Yuval; Fire, Michael; Herzberg, Amir; Shulman, Haya

    2014-12-01

    Online social networks (OSNs) have rapidly become a prominent and widely used service, offering a wealth of personal and sensitive information with significant security and privacy implications. Hence, OSNs are also an important--and popular--subject for research. To perform research based on real-life evidence, however, researchers may need to access OSN data, such as texts and files uploaded by users and connections among users. This raises significant ethical problems. Currently, there are no clear ethical guidelines, and researchers may end up (unintentionally) performing ethically questionable research, sometimes even when more ethical research alternatives exist. For example, several studies have employed "fake identities" to collect data from OSNs, but fake identities may be used for attacks and are considered a security issue. Is it legitimate to use fake identities for studying OSNs or for collecting OSN data for research? We present a taxonomy of the ethical challenges facing researchers of OSNs and compare different approaches. We demonstrate how ethical considerations have been taken into account in previous studies that used fake identities. In addition, several possible approaches are offered to reduce or avoid ethical misconducts. We hope this work will stimulate the development and use of ethical practices and methods in the research of online social networks.

  7. Analyzing the Impact of Storage Shortage on Data Availability in Decentralized Online Social Networks

    Directory of Open Access Journals (Sweden)

    Songling Fu

    2014-01-01

    Full Text Available Maintaining data availability is one of the biggest challenges in decentralized online social networks (DOSNs. The existing work often assumes that the friends of a user can always contribute to the sufficient storage capacity to store all data. However, this assumption is not always true in today’s online social networks (OSNs due to the fact that nowadays the users often use the smart mobile devices to access the OSNs. The limitation of the storage capacity in mobile devices may jeopardize the data availability. Therefore, it is desired to know the relation between the storage capacity contributed by the OSN users and the level of data availability that the OSNs can achieve. This paper addresses this issue. In this paper, the data availability model over storage capacity is established. Further, a novel method is proposed to predict the data availability on the fly. Extensive simulation experiments have been conducted to evaluate the effectiveness of the data availability model and the on-the-fly prediction.

  8. A network-based system of simulation, control and online assistance for HTR-10

    Energy Technology Data Exchange (ETDEWEB)

    Zhu Shutang [Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084 (China)], E-mail: zhust@tsinghua.edu.cn; Luo Shaojie; Shi Lei [Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084 (China)

    2008-07-15

    A network-based computer system has been developed for HTR-10. This system integrates three subsystems: the simulation subsystem (SIMUSUB), the visualized control designed subsystem (VCDSUB) and the online assistance subsystem (OASUB). The SIMUSUB consists of four functional elements: the simulation calculating server (SCS), the main control client (MCC), the data disposal client (DDC) and the results graphic display client (RGDC), all of which can communicate with each other via network. It is intended to analyze and calculate physical processes of the reactor core, the main loop system and the steam generator, etc., as well as to simulate the normal operational and transient accidents. The result data can be dynamically displayed through the RGDC. The VCDSUB provides a platform for control system modeling where the control flow systems can be automatically generated and graphically simulated. Based on the data from the field bus, the OASUB provides some of the reactor core parameters, which are difficult to measure. This integrated system can be used as an educational tool to understand the design and operational characteristics of the HTR-10, and can also provide online support for operators in the main control room, or as a convenient powerful tool for the control system design.

  9. A network-based system of simulation, control and online assistance for HTR-10

    International Nuclear Information System (INIS)

    Zhu Shutang; Luo Shaojie; Shi Lei

    2008-01-01

    A network-based computer system has been developed for HTR-10. This system integrates three subsystems: the simulation subsystem (SIMUSUB), the visualized control designed subsystem (VCDSUB) and the online assistance subsystem (OASUB). The SIMUSUB consists of four functional elements: the simulation calculating server (SCS), the main control client (MCC), the data disposal client (DDC) and the results graphic display client (RGDC), all of which can communicate with each other via network. It is intended to analyze and calculate physical processes of the reactor core, the main loop system and the steam generator, etc., as well as to simulate the normal operational and transient accidents. The result data can be dynamically displayed through the RGDC. The VCDSUB provides a platform for control system modeling where the control flow systems can be automatically generated and graphically simulated. Based on the data from the field bus, the OASUB provides some of the reactor core parameters, which are difficult to measure. This integrated system can be used as an educational tool to understand the design and operational characteristics of the HTR-10, and can also provide online support for operators in the main control room, or as a convenient powerful tool for the control system design

  10. Discovering the influential users oriented to viral marketing based on online social networks

    Science.gov (United States)

    Zhu, Zhiguo

    2013-08-01

    The target of viral marketing on the platform of popular online social networks is to rapidly propagate marketing information at lower cost and increase sales, in which a key problem is how to precisely discover the most influential users in the process of information diffusion. A novel method is proposed in this paper for helping companies to identify such users as seeds to maximize information diffusion in the viral marketing. Firstly, the user trust network oriented to viral marketing and users’ combined interest degree in the network including isolated users are extensively defined. Next, we construct a model considering the time factor to simulate the process of information diffusion in viral marketing and propose a dynamic algorithm description. Finally, experiments are conducted with a real dataset extracted from the famous SNS website Epinions. The experimental results indicate that the proposed algorithm has better scalability and is less time-consuming. Compared with the classical model, the proposed algorithm achieved a better performance than does the classical method on the two aspects of network coverage rate and time-consumption in our four sub-datasets.

  11. Qualities and Inequalities in Online Social Networks through the Lens of the Generalized Friendship Paradox.

    Science.gov (United States)

    Momeni, Naghmeh; Rabbat, Michael

    2016-01-01

    The friendship paradox is the phenomenon that in social networks, people on average have fewer friends than their friends do. The generalized friendship paradox is an extension to attributes other than the number of friends. The friendship paradox and its generalized version have gathered recent attention due to the information they provide about network structure and local inequalities. In this paper, we propose several measures of nodal qualities which capture different aspects of their activities and influence in online social networks. Using these measures we analyse the prevalence of the generalized friendship paradox over Twitter and we report high levels of prevalence (up to over 90% of nodes). We contend that this prevalence of the friendship paradox and its generalized version arise because of the hierarchical nature of the connections in the network. This hierarchy is nested as opposed to being star-like. We conclude that these paradoxes are collective phenomena not created merely by a minority of well-connected or high-attribute nodes. Moreover, our results show that a large fraction of individuals can experience the generalized friendship paradox even in the absence of a significant correlation between degrees and attributes.

  12. Efficacy of Online Social Networks on Language Teaching: A Bangladeshi Perspective

    Directory of Open Access Journals (Sweden)

    Shaila Shams

    2014-08-01

    Full Text Available It is now an established fact that the use of technology facilitates teaching and learning in language classrooms. With the advancement of technology, social networking websites have emerged too. Social networking sites have been quite popular among various age group users particularly the young users since their invention. Also, they are conceived to be able to motivate (Greenhow, Robelia, & Hughes, 2009 and expose learners to the authentic use of the target language (Baralt, 2011. However, very little research has been done, especially in Bangladesh, on how much these websites can contribute to language learning and teaching though they seem to offer ample opportunities. Therefore, this study aims at investigating the effect of using ‘The Facebook’, a social networking website, in language classrooms at tertiary level in Bangladesh. Participants of this study were first year first semester university students doing a foundation course in English focusing to improve their listening, speaking and writing skills. The participants were divided into two groups. Group 1 was the control group who was taught traditionally and non-digitally without using Facebook. Group 2, along with classroom teaching, received help from the instructor through Facebook and did tasks assigned on Facebook. At the end of the three months semester a test was taken and the result of both groups was compared. Thus, this study shall try to provide an answer regarding to what extent online social networks can facilitate second language acquisition.

  13. Qualities and Inequalities in Online Social Networks through the Lens of the Generalized Friendship Paradox.

    Directory of Open Access Journals (Sweden)

    Naghmeh Momeni

    Full Text Available The friendship paradox is the phenomenon that in social networks, people on average have fewer friends than their friends do. The generalized friendship paradox is an extension to attributes other than the number of friends. The friendship paradox and its generalized version have gathered recent attention due to the information they provide about network structure and local inequalities. In this paper, we propose several measures of nodal qualities which capture different aspects of their activities and influence in online social networks. Using these measures we analyse the prevalence of the generalized friendship paradox over Twitter and we report high levels of prevalence (up to over 90% of nodes. We contend that this prevalence of the friendship paradox and its generalized version arise because of the hierarchical nature of the connections in the network. This hierarchy is nested as opposed to being star-like. We conclude that these paradoxes are collective phenomena not created merely by a minority of well-connected or high-attribute nodes. Moreover, our results show that a large fraction of individuals can experience the generalized friendship paradox even in the absence of a significant correlation between degrees and attributes.

  14. Content-specific network analysis of peer-to-peer communication in an online community for smoking cessation.

    Science.gov (United States)

    Myneni, Sahiti; Cobb, Nathan K; Cohen, Trevor

    2016-01-01

    Analysis of user interactions in online communities could improve our understanding of health-related behaviors and inform the design of technological solutions that support behavior change. However, to achieve this we would need methods that provide granular perspective, yet are scalable. In this paper, we present a methodology for high-throughput semantic and network analysis of large social media datasets, combining semi-automated text categorization with social network analytics. We apply this method to derive content-specific network visualizations of 16,492 user interactions in an online community for smoking cessation. Performance of the categorization system was reasonable (average F-measure of 0.74, with system-rater reliability approaching rater-rater reliability). The resulting semantically specific network analysis of user interactions reveals content- and behavior-specific network topologies. Implications for socio-behavioral health and wellness platforms are also discussed.

  15. Online network of subspecialty aortic disease experts: Impact of "cloud" technology on management of acute aortic emergencies.

    Science.gov (United States)

    Schoenhagen, Paul; Roselli, Eric E; Harris, C Martin; Eagleton, Matthew; Menon, Venu

    2016-07-01

    For the management of acute aortic syndromes, regional treatment networks have been established to coordinate diagnosis and treatment between local emergency rooms and central specialized centers. Triage of acute aortic syndromes requires definitive imaging, resulting in complex data files. Modern information technology network structures, specifically "cloud" technology, coupled with mobile communication, increasingly support sharing of these data in a network of experts using mobile, online access and communication. Although this network is technically complex, the potential benefit of online sharing of data files between professionals at multiple locations within a treatment network appear obvious; however, clinical experience is limited, and further evaluation is needed. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

  16. How the Internet Facilitates the Activity within a Consumer Culture : - A Study of the Online Vinyl Record Network

    OpenAIRE

    Söderlindh, Stefan; Broman, David

    2009-01-01

    The purpose of this thesis is to describe and analyze how the online vinyl record network functions from both a consumer and retailer perspective, in order to gain an understanding of how the Internet facilitates the activity within a consumer culture. The vinyl record industry is experiencing a revival, with an upswing in sales and media attention and a significant increase in the amount of online trading. This inductive study contains data from qualitative interviews with ten vinyl record c...

  17. Analysis of Context Dependence in Social Interaction Networks of a Massively Multiplayer Online Role-Playing Game

    Science.gov (United States)

    Son, Seokshin; Kang, Ah Reum; Kim, Hyun-chul; Kwon, Taekyoung; Park, Juyong; Kim, Huy Kang

    2012-01-01

    Rapid advances in modern computing and information technology have enabled millions of people to interact online via various social network and gaming services. The widespread adoption of such online services have made possible analysis of large-scale archival data containing detailed human interactions, presenting a very promising opportunity to understand the rich and complex human behavior. In collaboration with a leading global provider of Massively Multiplayer Online Role-Playing Games (MMORPGs), here we present a network science-based analysis of the interplay between distinct types of user interaction networks in the virtual world. We find that their properties depend critically on the nature of the context-interdependence of the interactions, highlighting the complex and multilayered nature of human interactions, a robust understanding of which we believe may prove instrumental in the designing of more realistic future virtual arenas as well as provide novel insights to the science of collective human behavior. PMID:22496771

  18. Political campaigning 2.0: The influence of online news and social networking sites on attitudes and behavior

    Directory of Open Access Journals (Sweden)

    Montathar Faraon

    2014-11-01

    Full Text Available This study aimed to examine differences in influence between online news (e.g., New York Times and social networking sites (e.g., Facebook and Twitter on attitudes in political campaigns. In a web-based experiment, campaign, polls and election between two fictitious candidates were simulated. Participants’ explicit and implicit attitudes as well as voting behavior were assessed using self-report items and the Implicit Association Test (IAT. The results reveal that information emanating from online news had a significant influence on explicit and implicit attitudes while that of social networking sites did not. Overall, negative items had a stronger impact than positive ones, more so in online news compared to social networking sites. Negative information from either type of media was more likely to change participants’ explicit attitudes in a negative direction and as a consequence also change their vote. Practical implications of the findings and limitations of the study are discussed.

  19. Analysis of context dependence in social interaction networks of a massively multiplayer online role-playing game.

    Science.gov (United States)

    Son, Seokshin; Kang, Ah Reum; Kim, Hyun-chul; Kwon, Taekyoung; Park, Juyong; Kim, Huy Kang

    2012-01-01

    Rapid advances in modern computing and information technology have enabled millions of people to interact online via various social network and gaming services. The widespread adoption of such online services have made possible analysis of large-scale archival data containing detailed human interactions, presenting a very promising opportunity to understand the rich and complex human behavior. In collaboration with a leading global provider of Massively Multiplayer Online Role-Playing Games (MMORPGs), here we present a network science-based analysis of the interplay between distinct types of user interaction networks in the virtual world. We find that their properties depend critically on the nature of the context-interdependence of the interactions, highlighting the complex and multilayered nature of human interactions, a robust understanding of which we believe may prove instrumental in the designing of more realistic future virtual arenas as well as provide novel insights to the science of collective human behavior.

  20. Analysis of context dependence in social interaction networks of a massively multiplayer online role-playing game.

    Directory of Open Access Journals (Sweden)

    Seokshin Son

    Full Text Available Rapid advances in modern computing and information technology have enabled millions of people to interact online via various social network and gaming services. The widespread adoption of such online services have made possible analysis of large-scale archival data containing detailed human interactions, presenting a very promising opportunity to understand the rich and complex human behavior. In collaboration with a leading global provider of Massively Multiplayer Online Role-Playing Games (MMORPGs, here we present a network science-based analysis of the interplay between distinct types of user interaction networks in the virtual world. We find that their properties depend critically on the nature of the context-interdependence of the interactions, highlighting the complex and multilayered nature of human interactions, a robust understanding of which we believe may prove instrumental in the designing of more realistic future virtual arenas as well as provide novel insights to the science of collective human behavior.

  1. The relationship between online social networking and sexual risk behaviors among men who have sex with men (MSM.

    Directory of Open Access Journals (Sweden)

    Sean D Young

    Full Text Available Online social networking usage is growing rapidly, especially among at-risk populations, such as men who have sex with men (MSM. However, little research has studied the relationship between online social networking usage and sexual risk behaviors among at-risk populations. One hundred and eighteen Facebook-registered MSM (60.1% Latino, 28% African American; 11.9% other were recruited from online (social networking websites and banner advertisements and offline (local clinics, restaurants and organizations venues frequented by minority MSM. Inclusion criteria required participants to be men who were 18 years of age or older, had had sex with a man in the past 12 months, were living in Los Angeles, and had a Facebook account. Participants completed an online survey on their social media usage and sexual risk behaviors. Results from a multivariable regression suggest that number of sexual partners met from online social networking technologies is associated with increased: 1 likelihood of having exchanged sex for food, drugs, or a place to stay within the past 3 months; 2 number of new partners within the past 3 months; 3 number of male sex partners within the past 3 months; and 4 frequency of engaging in oral sex within the past 3 months, controlling for age, race, education, and total number of sexual partners. Understanding the relationship between social media sex-seeking and sexual risk behaviors among at-risk populations will help inform population-focused HIV prevention and treatment interventions.

  2. Using Pathfinder networks to discover alignment between expert and consumer conceptual knowledge from online vaccine content.

    Science.gov (United States)

    Amith, Muhammad; Cunningham, Rachel; Savas, Lara S; Boom, Julie; Schvaneveldt, Roger; Tao, Cui; Cohen, Trevor

    2017-10-01

    This study demonstrates the use of distributed vector representations and Pathfinder Network Scaling (PFNETS) to represent online vaccine content created by health experts and by laypeople. By analyzing a target audience's conceptualization of a topic, domain experts can develop targeted interventions to improve the basic health knowledge of consumers. The underlying assumption is that the content created by different groups reflects the mental organization of their knowledge. Applying automated text analysis to this content may elucidate differences between the knowledge structures of laypeople (heath consumers) and professionals (health experts). This paper utilizes vaccine information generated by laypeople and health experts to investigate the utility of this approach. We used an established technique from cognitive psychology, Pathfinder Network Scaling to infer the structure of the associational networks between concepts learned from online content using methods of distributional semantics. In doing so, we extend the original application of PFNETS to infer knowledge structures from individual participants, to infer the prevailing knowledge structures within communities of content authors. The resulting graphs reveal opportunities for public health and vaccination education experts to improve communication and intervention efforts directed towards health consumers. Our efforts demonstrate the feasibility of using an automated procedure to examine the manifestation of conceptual models within large bodies of free text, revealing evidence of conflicting understanding of vaccine concepts among health consumers as compared with health experts. Additionally, this study provides insight into the differences between consumer and expert abstraction of domain knowledge, revealing vaccine-related knowledge gaps that suggest opportunities to improve provider-patient communication. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Improving Stability and Convergence for Adaptive Radial Basis Function Neural Networks Algorithm. (On-Line Harmonics Estimation Application

    Directory of Open Access Journals (Sweden)

    Eyad K Almaita

    2017-03-01

    Keywords: Energy efficiency, Power quality, Radial basis function, neural networks, adaptive, harmonic. Article History: Received Dec 15, 2016; Received in revised form Feb 2nd 2017; Accepted 13rd 2017; Available online How to Cite This Article: Almaita, E.K and Shawawreh J.Al (2017 Improving Stability and Convergence for Adaptive Radial Basis Function Neural Networks Algorithm (On-Line Harmonics Estimation Application.  International Journal of Renewable Energy Develeopment, 6(1, 9-17. http://dx.doi.org/10.14710/ijred.6.1.9-17

  4. To Enhance Collaborative Learning and Practice Network Knowledge with a Virtualization Laboratory and Online Synchronous Discussion

    Directory of Open Access Journals (Sweden)

    Wu-Yuin Hwang

    2014-09-01

    Full Text Available Recently, various computer networking courses have included additional laboratory classes in order to enhance students’ learning achievement. However, these classes need to establish a suitable laboratory where each student can connect network devices to configure and test functions within different network topologies. In this case, the Linux operating system can be used to operate network devices and the virtualization technique can include multiple OSs for supporting a significant number of students. In previous research, the virtualization application was successfully applied in a laboratory, but focused only on individual assignments. The present study extends previous research by designing the Networking Virtualization-Based Laboratory (NVBLab, which requires collaborative learning among the experimental students. The students were divided into an experimental group and a control group for the experiment. The experimental group performed their laboratory assignments using NVBLab, whereas the control group completed them on virtual machines (VMs that were installed on their personal computers. Moreover, students using NVBLab were provided with an online synchronous discussion (OSD feature that enabled them to communicate with others. The laboratory assignments were divided into two parts: Basic Labs and Advanced Labs. The results show that the experimental group significantly outperformed the control group in two Advanced Labs and the post-test after Advanced Labs. Furthermore, the experimental group’s activities were better than those of the control group based on the total average of the command count per laboratory. Finally, the findings of the interviews and questionnaires with the experimental group reveal that NVBLab was helpful during and after laboratory class.

  5. Structural and dynamical patterns on online social networks: the Spanish May 15th movement as a case study.

    Directory of Open Access Journals (Sweden)

    Javier Borge-Holthoefer

    Full Text Available The number of people using online social networks in their everyday life is continuously growing at a pace never saw before. This new kind of communication has an enormous impact on opinions, cultural trends, information spreading and even in the commercial success of new products. More importantly, social online networks have revealed as a fundamental organizing mechanism in recent country-wide social movements. In this paper, we provide a quantitative analysis of the structural and dynamical patterns emerging from the activity of an online social network around the ongoing May 15th (15M movement in Spain. Our network is made up by users that exchanged tweets in a time period of one month, which includes the birth and stabilization of the 15M movement. We characterize in depth the growth of such dynamical network and find that it is scale-free with communities at the mesoscale. We also find that its dynamics exhibits typical features of critical systems such as robustness and power-law distributions for several quantities. Remarkably, we report that the patterns characterizing the spreading dynamics are asymmetric, giving rise to a clear distinction between information sources and sinks. Our study represents a first step towards the use of data from online social media to comprehend modern societal dynamics.

  6. Structural and dynamical patterns on online social networks: the Spanish May 15th movement as a case study.

    Science.gov (United States)

    Borge-Holthoefer, Javier; Rivero, Alejandro; García, Iñigo; Cauhé, Elisa; Ferrer, Alfredo; Ferrer, Darío; Francos, David; Iñiguez, David; Pérez, María Pilar; Ruiz, Gonzalo; Sanz, Francisco; Serrano, Fermín; Viñas, Cristina; Tarancón, Alfonso; Moreno, Yamir

    2011-01-01

    The number of people using online social networks in their everyday life is continuously growing at a pace never saw before. This new kind of communication has an enormous impact on opinions, cultural trends, information spreading and even in the commercial success of new products. More importantly, social online networks have revealed as a fundamental organizing mechanism in recent country-wide social movements. In this paper, we provide a quantitative analysis of the structural and dynamical patterns emerging from the activity of an online social network around the ongoing May 15th (15M) movement in Spain. Our network is made up by users that exchanged tweets in a time period of one month, which includes the birth and stabilization of the 15M movement. We characterize in depth the growth of such dynamical network and find that it is scale-free with communities at the mesoscale. We also find that its dynamics exhibits typical features of critical systems such as robustness and power-law distributions for several quantities. Remarkably, we report that the patterns characterizing the spreading dynamics are asymmetric, giving rise to a clear distinction between information sources and sinks. Our study represents a first step towards the use of data from online social media to comprehend modern societal dynamics.

  7. A neural network device for on-line particle identification in cosmic ray experiments

    International Nuclear Information System (INIS)

    Scrimaglio, R.; Finetti, N.; D'Altorio, L.; Rantucci, E.; Raso, M.; Segreto, E.; Tassoni, A.; Cardarilli, G.C.

    2004-01-01

    On-line particle identification is one of the main goals of many experiments in space both for rare event studies and for optimizing measurements along the orbital trajectory. Neural networks can be a useful tool for signal processing and real time data analysis in such experiments. In this document we report on the performances of a programmable neural device which was developed in VLSI analog/digital technology. Neurons and synapses were accomplished by making use of Operational Transconductance Amplifier (OTA) structures. In this paper we report on the results of measurements performed in order to verify the agreement of the characteristic curves of each elementary cell with simulations and on the device performances obtained by implementing simple neural structures on the VLSI chip. A feed-forward neural network (Multi-Layer Perceptron, MLP) was implemented on the VLSI chip and trained to identify particles by processing the signals of two-dimensional position-sensitive Si detectors. The radiation monitoring device consisted of three double-sided silicon strip detectors. From the analysis of a set of simulated data it was found that the MLP implemented on the neural device gave results comparable with those obtained with the standard method of analysis confirming that the implemented neural network could be employed for real time particle identification

  8. Learning from Your Network of Friends: A Trajectory Representation Learning Model Based on Online Social Ties

    KAUST Repository

    Alharbi, Basma Mohammed; Zhang, Xiangliang

    2017-01-01

    Location-Based Social Networks (LBSNs) capture individuals whereabouts for a large portion of the population. To utilize this data for user (location)-similarity based tasks, one must map the raw data into a low-dimensional uniform feature space. However, due to the nature of LBSNs, many users have sparse and incomplete check-ins. In this work, we propose to overcome this issue by leveraging the network of friends, when learning the new feature space. We first analyze the impact of friends on individuals's mobility, and show that individuals trajectories are correlated with thoseof their friends and friends of friends (2-hop friends) in an online setting. Based on our observation, we propose a mixed-membership model that infers global mobility patterns from users' check-ins and their network of friends, without impairing the model's complexity. Our proposed model infers global patterns and learns new representations for both usersand locations simultaneously. We evaluate the inferred patterns and compare the quality of the new user representation against baseline methods on a social link prediction problem.

  9. An Optimal Online Resource Allocation Algorithm for Energy Harvesting Body Area Networks

    Directory of Open Access Journals (Sweden)

    Guangyuan Wu

    2018-01-01

    Full Text Available In Body Area Networks (BANs, how to achieve energy management to extend the lifetime of the body area networks system is one of the most critical problems. In this paper, we design a body area network system powered by renewable energy, in which the sensors carried by patient with energy harvesting module can transmit data to a personal device. We do not require any a priori knowledge of the stochastic nature of energy harvesting and energy consumption. We formulate a user utility optimization problem. We use Lyapunov Optimization techniques to decompose the problem into three sub-problems, i.e., battery management, collecting rate control and transmission power allocation. We propose an online resource allocation algorithm to achieve two major goals: (1 balancing sensors’ energy harvesting and energy consumption while stabilizing the BANs system; and (2 maximizing the user utility. Performance analysis addresses required battery capacity, bounded data queue length and optimality of the proposed algorithm. Simulation results verify the optimization of algorithm.

  10. Posting Behaviour Patterns in an Online Smoking Cessation Social Network: Implications for Intervention Design and Development

    Science.gov (United States)

    Healey, Benjamin; Hoek, Janet; Edwards, Richard

    2014-01-01

    Objectives Online Cessation Support Networks (OCSNs) are associated with increased quit success rates, but few studies have examined their use over time. We identified usage patterns in New Zealand's largest OCSN over two years and explored implications for OCSN intervention design and evaluation. Methods We analysed metadata relating to 133,096 OCSN interactions during 2011 and 2012. Metrics covered aggregate network activity, user posting activity and longevity, and between-user commenting. Binary logistic regression models were estimated to investigate the feasibility of predicting low user engagement using early interaction data. Results Repeating periodic peaks and troughs in aggregate activity related not only to seasonality (e.g., New Year), but also to day of the week. Out of 2,062 unique users, 69 Highly Engaged Users (180+ interactions each) contributed 69% of all OCSN interactions in 2012 compared to 1.3% contributed by 864 Minimally Engaged Users (metrics including posts and comments, this change did not coincide with large gains in first-time user persistence. Researchers assessing intervention effects should therefore examine multiple measures when evaluating changes in network dynamics over time. PMID:25192174

  11. Online network organization of Barcelona en Comú, an emergent movement-party.

    Science.gov (United States)

    Aragón, Pablo; Gallego, Helena; Laniado, David; Volkovich, Yana; Kaltenbrunner, Andreas

    2017-01-01

    The emerging grassroots party Barcelona en Comú won the 2015 Barcelona City Council election. This candidacy was devised by activists involved in the Spanish 15M movement to transform citizen outrage into political change. On the one hand, the 15M movement was based on a decentralized structure. On the other hand, political science literature postulates that parties develop oligarchical leadership structures. This tension motivates to examine whether Barcelona en Comú preserved a decentralized structure or adopted a conventional centralized organization. In this study we develop a computational methodology to characterize the online network organization of every party in the election campaign on Twitter. Results on the network of retweets reveal that, while traditional parties are organized in a single cluster, for Barcelona en Comú two well-defined groups co-exist: a centralized cluster led by the candidate and party accounts, and a decentralized cluster with the movement activists. Furthermore, results on the network of replies also shows a dual structure: a cluster around the candidate receiving the largest attention from other parties, and another with the movement activists exhibiting a higher predisposition to dialogue with other parties.

  12. Optimal Channel Selection Based on Online Decision and Offline Learning in Multichannel Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Mu Qiao

    2017-01-01

    Full Text Available We propose a channel selection strategy with hybrid architecture, which combines the centralized method and the distributed method to alleviate the overhead of access point and at the same time provide more flexibility in network deployment. By this architecture, we make use of game theory and reinforcement learning to fulfill the optimal channel selection under different communication scenarios. Particularly, when the network can satisfy the requirements of energy and computational costs, the online decision algorithm based on noncooperative game can help each individual sensor node immediately select the optimal channel. Alternatively, when the network cannot satisfy the requirements of energy and computational costs, the offline learning algorithm based on reinforcement learning can help each individual sensor node to learn from its experience and iteratively adjust its behavior toward the expected target. Extensive simulation results validate the effectiveness of our proposal and also prove that higher system throughput can be achieved by our channel selection strategy over the conventional off-policy channel selection approaches.

  13. Online Learning Algorithm for Time Series Forecasting Suitable for Low Cost Wireless Sensor Networks Nodes

    Directory of Open Access Journals (Sweden)

    Juan Pardo

    2015-04-01

    Full Text Available Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network. The present paper uses a Wireless Sensor Networks (WSN to monitor and forecast the indoor temperature in a smart home, based on low resources and cost microcontroller technology as the 8051MCU. An on-line learning approach, based on Back-Propagation (BP algorithm for ANNs, has been developed for real-time time series learning. It performs the model training with every new data that arrive to the system, without saving enormous quantities of data to create a historical database as usual, i.e., without previous knowledge. Consequently to validate the approach a simulation study through a Bayesian baseline model have been tested in order to compare with a database of a real application aiming to see the performance and accuracy. The core of the paper is a new algorithm, based on the BP one, which has been described in detail, and the challenge was how to implement a computational demanding algorithm in a simple architecture with very few hardware resources.

  14. Online Learning Algorithm for Time Series Forecasting Suitable for Low Cost Wireless Sensor Networks Nodes

    Science.gov (United States)

    Pardo, Juan; Zamora-Martínez, Francisco; Botella-Rocamora, Paloma

    2015-01-01

    Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning) systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN) algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network. The present paper uses a Wireless Sensor Networks (WSN) to monitor and forecast the indoor temperature in a smart home, based on low resources and cost microcontroller technology as the 8051MCU. An on-line learning approach, based on Back-Propagation (BP) algorithm for ANNs, has been developed for real-time time series learning. It performs the model training with every new data that arrive to the system, without saving enormous quantities of data to create a historical database as usual, i.e., without previous knowledge. Consequently to validate the approach a simulation study through a Bayesian baseline model have been tested in order to compare with a database of a real application aiming to see the performance and accuracy. The core of the paper is a new algorithm, based on the BP one, which has been described in detail, and the challenge was how to implement a computational demanding algorithm in a simple architecture with very few hardware resources. PMID:25905698

  15. Actual versus perceived peer sexual risk behavior in online youth social networks.

    Science.gov (United States)

    Black, Sandra R; Schmiege, Sarah; Bull, Sheana

    2013-09-01

    Perception of peer behaviors is an important predictor of actual risk behaviors among youth. However, we lack understanding of peer influence through social media and of actual and perceived peer behavior concordance. The purpose of this research is to document the relationship between individual perception of and actual peer sexual risk behavior using online social networks. The data are a result of a secondary analysis of baseline self-reported and peer-reported sexual risk behavior from a cluster randomized trial including 1,029 persons from 162 virtual networks. Individuals (seeds) recruited up to three friends who then recruited additional friends, extending three waves from the seed. ANOVA models compared network means of actual participant behavior across categories of perceived behavior. Concordance varied between reported and perceived behavior, with higher concordance between perceived and reported condom use, multiple partners, concurrent partners, sexual pressure, and drug and alcohol use during sex. Individuals significantly over-reported risk and under-reported protective peer behaviors related to sex.

  16. Online identity: constructing interpersonal trust and openness through participating in hospitality social networks

    Directory of Open Access Journals (Sweden)

    Alexander Ronzhyn

    2013-06-01

    Full Text Available The present article describes the results of research on online identity construction during the participation in the hospitality social networks. Specifically the user references are analysed to understand patterns that form the image of a member. CouchSurfing service (couchsurfing.org allows users to leave short texts where the experience of hosting/being hosted by a CS member is described, is an evaluation of the CS members of each other’s personal traits, skills and common experience. Therefore references can become a good instrument for portraying a CouchSurfing member and understanding his or her particular traits. References form an important part of a user’s virtual identity in the network. Using a sample of references of Spanish CouchSurfing users, the research established main characteristics of the references, which are the openness, readiness to share ideas and experiences and trustworthiness. These concepts illustrate the typical traits associated with a user of the network and also shed light on the activities common during offl ine CS meetings

  17. Subtle role of latency for information diffusion in online social networks

    International Nuclear Information System (INIS)

    Xiong Fei; Wang Xi-Meng; Cheng Jun-Jun

    2016-01-01

    Information diffusion in online social networks is induced by the event of forwarding information for users, and latency exists widely in user spreading behaviors. Little work has been done to reveal the effect of latency on the diffusion process. In this paper, we propose a propagation model in which nodes may suspend their spreading actions for a waiting period of stochastic length. These latent nodes may recover their activity again. Meanwhile, the mechanism of forwarding information is also introduced into the diffusion model. Mean-field analysis and numerical simulations indicate that our model has three nontrivial results. First, the spreading threshold does not correlate with latency in neither homogeneous nor heterogeneous networks, but depends on the spreading and refractory parameter. Furthermore, latency affects the diffusion process and changes the infection scale. A large or small latency parameter leads to a larger final diffusion extent, but the intrinsic dynamics is different. Large latency implies forwarding information rapidly, while small latency prevents nodes from dropping out of interactions. In addition, the betweenness is a better descriptor to identify influential nodes in the model with latency, compared with the coreness and degree. These results are helpful in understanding some collective phenomena of the diffusion process and taking measures to restrain a rumor in social networks. (paper)

  18. Online learning algorithm for time series forecasting suitable for low cost wireless sensor networks nodes.

    Science.gov (United States)

    Pardo, Juan; Zamora-Martínez, Francisco; Botella-Rocamora, Paloma

    2015-04-21

    Time series forecasting is an important predictive methodology which can be applied to a wide range of problems. Particularly, forecasting the indoor temperature permits an improved utilization of the HVAC (Heating, Ventilating and Air Conditioning) systems in a home and thus a better energy efficiency. With such purpose the paper describes how to implement an Artificial Neural Network (ANN) algorithm in a low cost system-on-chip to develop an autonomous intelligent wireless sensor network. The present paper uses a Wireless Sensor Networks (WSN) to monitor and forecast the indoor temperature in a smart home, based on low resources and cost microcontroller technology as the 8051MCU. An on-line learning approach, based on Back-Propagation (BP) algorithm for ANNs, has been developed for real-time time series learning. It performs the model training with every new data that arrive to the system, without saving enormous quantities of data to create a historical database as usual, i.e., without previous knowledge. Consequently to validate the approach a simulation study through a Bayesian baseline model have been tested in order to compare with a database of a real application aiming to see the performance and accuracy. The core of the paper is a new algorithm, based on the BP one, which has been described in detail, and the challenge was how to implement a computational demanding algorithm in a simple architecture with very few hardware resources.

  19. Learning from Your Network of Friends: A Trajectory Representation Learning Model Based on Online Social Ties

    KAUST Repository

    Alharbi, Basma Mohammed

    2017-02-07

    Location-Based Social Networks (LBSNs) capture individuals whereabouts for a large portion of the population. To utilize this data for user (location)-similarity based tasks, one must map the raw data into a low-dimensional uniform feature space. However, due to the nature of LBSNs, many users have sparse and incomplete check-ins. In this work, we propose to overcome this issue by leveraging the network of friends, when learning the new feature space. We first analyze the impact of friends on individuals\\'s mobility, and show that individuals trajectories are correlated with thoseof their friends and friends of friends (2-hop friends) in an online setting. Based on our observation, we propose a mixed-membership model that infers global mobility patterns from users\\' check-ins and their network of friends, without impairing the model\\'s complexity. Our proposed model infers global patterns and learns new representations for both usersand locations simultaneously. We evaluate the inferred patterns and compare the quality of the new user representation against baseline methods on a social link prediction problem.

  20. Social Networks Used by Teens and Parental Control of Their Online Communication

    Directory of Open Access Journals (Sweden)

    M. Shehu

    2017-06-01

    Full Text Available The Internet plays important functions in identity formation, personal autono-my, and relationships outside the family. It allows teens to develop their own interests, to identify with others. The aim of the study is to present concrete evidence regarding to the communication through social networks and parental care in the management of online communication. Referring questionnaire “Student Needs Assessment Survey” by N. E. Willard (2007, but the author has selected questions to the scope of its study. The sample of the study includes 255 pupils aged 15 – 19 (110 Male and 145 Female. The statistical data processing was performed by SPPS statistical program, version 20. Cronbach’s Alpha 0.764 were used to assess the reliability of the instrument. The most favorite activity on the Internet by the teens is navigation on the In-ternet to see/learn new things (68.6%, during the week the subjects spend ap-proximately less than 2 hours per day (34.1% of them. Most of teenagers (82.7% claims to have communication with their parents about how they treats their friends and 56.5% of them say that sometimes have control by their par-ents for what they do online. If pupils would victim of pressure on the internet and do not have opportunities to can be contained by those 69% of them approve that they would tell to their parents and also (63.9% to school staff members. When there have been cases of violence, even threatening suicide rate of reporting and collaboration between parent - teacher is high, while in other elements resulting lower interest rates. One of the main factors in man-agement of this online communication and Internet is the parent care, which is considered most important in terms of education and not only.

  1. Effect of users' opinion evolution on information diffusion in online social networks

    Science.gov (United States)

    Zhu, Hengmin; Kong, Yuehan; Wei, Jing; Ma, Jing

    2018-02-01

    The process of topic propagation always interweaves information diffusion and opinion evolution, but most previous works studied the models of information diffusion and opinion evolution separately, and seldom focused on their interaction of each other. To shed light on the effect of users' opinion evolution on information diffusion in online social networks, we proposed a model which incorporates opinion evolution into the process of topic propagation. Several real topics propagating on Sina Microblog were collected to analyze individuals' propagation intentions, and different propagation intentions were considered in the model. The topic propagation was simulated to explore the impact of different opinion distributions and intervention with opposite opinion on information diffusion. Results show that the topic with one-sided opinions can spread faster and more widely, and intervention with opposite opinion is an effective measure to guide the topic propagation. The earlier to intervene, the more effectively the topic propagation would be guided.

  2. African American Social Networking Online: Applying a Digital Practice Approach to Understanding Digital Inequalities

    Directory of Open Access Journals (Sweden)

    Danielle Taana Smith

    2013-06-01

    Full Text Available This study develops a framework for systematic examination of information and communication technologies (ICTs usage differences within a group. This framework situates the digital divide and digital inequalities model within a broader conceptual model of digital practice, exemplified by how groups of people use ICTs. I use nationally representative data to examine online activities on social networking sites (SNS for African Americans and other ethnoracial groups. The data for this research comes from the Pew Internet and American Life’s “Spring Tracking Survey 2008”. The results from regression analyses support the digital practice framework which moves discussions of ICT usage beyond social and economic advantages or disadvantages, and addresses individual and group needs in using these technologies.

  3. SMEs Going Global: A Comparison of the Internationalization Strategies of Publishers and Online Social Networks

    Directory of Open Access Journals (Sweden)

    Bettina Lis

    2012-01-01

    Full Text Available Up to now, most research has been conducted on the internationalization strategies of large media companies and groups. But tapping new foreign markets is also relevant to small- and medium-sized enterprises (SMEs of all media sectors. This paper therefore focuses on the internationalization strategies of different types of media SMEs. It aims at describing and comparing the motives for becoming an international player as well as the specific market selection, market entry, and market development strategies. Furthermore, it focuses on the main organizational implications. On the basis of a multiple-case design we compare two German regional newspaper publishers with two German special interest publishers and two online social business networks. Results show similarities and differences between these media sectors according to the nature of the media businesses. The cases also highlight the importance of international management skills also in the context of SMEs.

  4. How risky are social networking sites? A comparison of places online where youth sexual solicitation and harassment occurs.

    Science.gov (United States)

    Ybarra, Michele L; Mitchell, Kimberly J

    2008-02-01

    Recently, public attention has focused on the possibility that social networking sites such as MySpace and Facebook are being widely used to sexually solicit underage youth, consequently increasing their vulnerability to sexual victimization. Beyond anecdotal accounts, however, whether victimization is more commonly reported in social networking sites is unknown. The Growing up With Media Survey is a national cross-sectional online survey of 1588 youth. Participants were 10- to 15-year-old youth who have used the Internet at least once in the last 6 months. The main outcome measures were unwanted sexual solicitation on the Internet, defined as unwanted requests to talk about sex, provide personal sexual information, and do something sexual, and Internet harassment, defined as rude or mean comments, or spreading of rumors. Fifteen percent of all of the youth reported an unwanted sexual solicitation online in the last year; 4% reported an incident on a social networking site specifically. Thirty-three percent reported an online harassment in the last year; 9% reported an incident on a social networking site specifically. Among targeted youth, solicitations were more commonly reported via instant messaging (43%) and in chat rooms (32%), and harassment was more commonly reported in instant messaging (55%) than through social networking sites (27% and 28%, respectively). Broad claims of victimization risk, at least defined as unwanted sexual solicitation or harassment, associated with social networking sites do not seem justified. Prevention efforts may have a greater impact if they focus on the psychosocial problems of youth instead of a specific Internet application, including funding for online youth outreach programs, school antibullying programs, and online mental health services.

  5. A fast and accurate online sequential learning algorithm for feedforward networks.

    Science.gov (United States)

    Liang, Nan-Ying; Huang, Guang-Bin; Saratchandran, P; Sundararajan, N

    2006-11-01

    In this paper, we develop an online sequential learning algorithm for single hidden layer feedforward networks (SLFNs) with additive or radial basis function (RBF) hidden nodes in a unified framework. The algorithm is referred to as online sequential extreme learning machine (OS-ELM) and can learn data one-by-one or chunk-by-chunk (a block of data) with fixed or varying chunk size. The activation functions for additive nodes in OS-ELM can be any bounded nonconstant piecewise continuous functions and the activation functions for RBF nodes can be any integrable piecewise continuous functions. In OS-ELM, the parameters of hidden nodes (the input weights and biases of additive nodes or the centers and impact factors of RBF nodes) are randomly selected and the output weights are analytically determined based on the sequentially arriving data. The algorithm uses the ideas of ELM of Huang et al. developed for batch learning which has been shown to be extremely fast with generalization performance better than other batch training methods. Apart from selecting the number of hidden nodes, no other control parameters have to be manually chosen. Detailed performance comparison of OS-ELM is done with other popular sequential learning algorithms on benchmark problems drawn from the regression, classification and time series prediction areas. The results show that the OS-ELM is faster than the other sequential algorithms and produces better generalization performance.

  6. Engagement, compliance and retention with a gamified online social networking physical activity intervention.

    Science.gov (United States)

    Ryan, Jillian; Edney, Sarah; Maher, Carol

    2017-12-01

    Health behaviour interventions delivered via online social networks are an increasingly popular approach to addressing lifestyle-related health problems. However, research to date consistently reports poor user engagement and retention. The current study examined user engagement, compliance and retention with Active Team-a gamified physical activity intervention delivered by via an online Facebook application. Associations between engagement and participant (n = 51) demographic and team characteristics (sex, age, education and team size) were examined, as well as temporal trends in engagement during the 50-day intervention. Analyses revealed significant associations between both engagement (p = <0.001) and gamification (p = 0.04) with education, with participants in the middle education category appearing to have the highest rates of engagement and use of gamification features. Gender was also related to engagement, with males demonstrating the highest use of the intervention's gamification features (p = 0.004). Although compliance was consistently high for the duration, engagement declined steadily throughout the intervention. Engagement peaked on Wednesdays, coinciding with the delivery of a customised email reminder. Findings reveal individual differences in engagement with Active Team, highlighting a need to tailor interventions to the target audience. Gamification features may enhance engagement amongst males, who are traditionally recognised as a difficult demographic group to engage. Finally, the use of customised, periodic push reminders delivered by email may enhance user engagement by drawing them back to the intervention and helping to sustain intervention behaviours.

  7. Online social networking sites-a novel setting for health promotion?

    Science.gov (United States)

    Loss, Julika; Lindacher, Verena; Curbach, Janina

    2014-03-01

    Among adolescents, online social networking sites (SNS) such as Facebook are popular platforms for social interaction and may therefore be considered as 'novel settings' that could be exploited for health promotion. In this article, we examine the relevant definitions in health promotion and literature in order to analyze whether key characteristics of 'settings for health promotion' and the socio-ecological settings approach can be transferred to SNS. As many of our daily activities have shifted to cyberspace, we argue that online social interaction may gain more importance than geographic closeness for defining a 'setting'. While exposition to positive references to risk behavior by peers may render the SNS environment detrimental to health, SNS may allow people to create their own content and therefore foster participation. However, those health promotion projects delivered on SNS up until today solely relied on health education directed at end users. It remains unclear how health promotion on SNS can meet other requirements of the settings approach (e.g. building partnerships, changing the environment). As yet, one should be cautious in terming SNS a 'setting'. Copyright © 2013 Elsevier Ltd. All rights reserved.

  8. Energy Efficient Power Allocation in Multi-tier 5G Networks Using Enhanced Online Learning

    KAUST Repository

    Alqerm, Ismail

    2017-07-25

    The multi-tier heterogeneous structure of 5G with dense small cells deployment, relays, and device-to-device (D2D) communications operating in an underlay fashion is envisioned as a potential solution to satisfy the future demand for cellular services. However, efficient power allocation among dense secondary transmitters that maintains quality of service (QoS) for macro (primary) cell users and secondary cell users is a critical challenge for operating such radio. In this paper, we focus on the power allocation problem in the multi-tier 5G network structure using a non-cooperative methodology with energy efficiency consideration. Therefore, we propose a distributive intuition-based online learning scheme for power allocation in the downlink of the 5G systems, where each transmitter surmises other transmitters power allocation strategies without information exchange. The proposed learning model exploits a brief state representation to account for the problem of dimensionality in online learning and expedite the convergence. The convergence of the proposed scheme is proved and numerical results demonstrate its capability to achieve fast convergence with QoS guarantee and significant improvement in system energy efficiency.

  9. Teleaudiology: efficacy assessment of an online social network as a support tool for parents of children candidates for cochlear implant.

    Science.gov (United States)

    Aiello, Camila Piccini; Ferrari, Deborah Viviane

    2015-01-01

    To assess the efficacy of an online social network as a support for parents of children with hearing impairment. Twenty-two mothers, randomly divided into experimental (n=11) and control (n=11) groups, filled in an online form containing the Parental Stress Index - Short Form (PSI-SF). Only the experimental group had access to the "Babies' Portal" social network. Both groups filled in the online form once again 3 months after the first assessment, for evaluating the use and participation in the social network. The posts on the social network were rated by two independent raters regarding themes and mechanisms of self-help. No difference was observed in mean PSI-SF scores between the groups for both assessments. Intragroup analysis showed no difference for total and subscale results of PSI-SF between the two data collected for both groups except for the "Defensive Response" subscale, in which a decrease was observed in the score for the control group. The most frequent posting themes were related to personal information and expressions of religious beliefs. Regarding self-help mechanisms, a higher frequency of exchanging experiences and gratitude expressions was observed. Participants in the experimental group stated they would have liked to participate more frequently in the social network as they considered this tool important because of the exchange of information and experience with other mothers and hearing health-care professionals. The posts and the assessment of participants indicated the potential of this network to support parents of children with hearing impairment.

  10. ONLINE SOCIAL NETWORKS AS A TOOL FOR THE PROMOTION OF PHYSICAL ACTIVITY AND HEALTH: A RESOURCE SCIENTIFICALLY FEW EXPLORED

    Directory of Open Access Journals (Sweden)

    Arían Ramón Aladro Gonzalvo

    2015-06-01

    Full Text Available Due to the great impact  that are exerting the networks in society, it is crucial to know the features that distinguish online social networks bringing together users interested in receiving information and resources to improve or maintain the body in shape. This article aims to comment on the limited research interested in studying the features and particularities of online communities that provide information, advice and support in the execution, performance and promotion of the health and fitness activities. Particularly, it underline about the necessity to know of networks structure, user profiles and peer-to-peer interaction, sort of membership, mechanisms of communication, representation of the body image and patterns of association. Likewise, the size of the support networks, telepresence, technology acceptance and perceived risk on the network. Besides, we recommend exploring two Fitness-related online social networks. Finally, it makes known the recurring problems in the analysis in order to characterize psychosocial and communicative aspects of users in the virtual environment.

  11. Modeling individual and collective opinion in online social networks: drivers of choice behavior and effects of marketing interventions

    NARCIS (Netherlands)

    Koster, S.E.; Langley, D.J.

    2013-01-01

    We investigate factors influencing choice behavior in online social networks. We use twitter data from a Dutch television talent show. In study one, we implement a nested conditional logit model with latent classes. We find heterogeneous effects. For two latent classes, cognitive factors most

  12. Online social networking in adolescence: patterns of use in six European countries and links with psychosocial functioning.

    NARCIS (Netherlands)

    Tsitsika, A.K.; Tzavela, E.C.; Janikian, M.; Olafsson, K.; Iordache, A.; Schoenmakers, T.M.; Tzavara, C.; Richardson, C.

    2014-01-01

    Purpose: Online communication tools, such as social networking sites (SNS), have been comprehensively embraced by adolescents and have become a dominant daily social practice. Recognizing SNS as a key context of adolescent development, this study aimed to investigate associations between heavier SNS

  13. Conversational Scholarship in Cyberspace: The Evolution and Activities of H-Net, the Online Network for the Humanities.

    Science.gov (United States)

    Turnbull, Paul

    1996-01-01

    The origins and current use of H-Net, an online humanities network on the World Wide Web, are examined. H-Net currently sponsors 73 electronic discussion lists that reach subscribers in 68 countries. Discussion groups have not met expectations for scholarly exchange, possibly because of plagiarism and copyright concerns. New ventures include book…

  14. Development and Analyses of Privacy Management Models in Online Social Networks Based on Communication Privacy Management Theory

    Science.gov (United States)

    Lee, Ki Jung

    2013-01-01

    Online social networks (OSNs), while serving as an emerging means of communication, promote various issues of privacy. Users of OSNs encounter diverse occasions that lead to invasion of their privacy, e.g., published conversation, public revelation of their personally identifiable information, and open boundary of distinct social groups within…

  15. More Questions than Answers: Assessing the Impact of Online Social Networking on a Service-Learning Project

    Science.gov (United States)

    Moeller, Mary R.; Nagy, Dianne

    2013-01-01

    This article details the evolution and results of a service-learning project designed to extend cross-cultural relationships via online social networking between students at a U.S. Bureau of Indian Education boarding school and teacher candidates in a required diversity course. The goals for the partnership included helping Native American…

  16. Online teaching of inflammatory skin pathology by a French-speaking International University Network.

    Science.gov (United States)

    Perron, Emilie; Battistella, Maxime; Vergier, Béatrice; Fiche, Maryse; Bertheau, Philippe; Têtu, Bernard

    2014-01-01

    Developments in technology, web-based teaching and whole slide imaging have broadened the teaching horizon in anatomic pathology. Creating online learning material including many types of media such as radiologic images, whole slides, videos, clinical and macroscopic photographs, is now accessible to most universities. Unfortunately, a major limiting factor to maintain and update the learning material is the amount of resources needed. In this perspective, a French-national university network was initiated in 2011 to build joint online teaching modules consisting of clinical cases and tests. The network has since expanded internationally to Québec, Switzerland and Ivory Coast. One of the first steps of the project was to build a learning module on inflammatory skin pathology for interns and residents in pathology and dermatology. A pathology resident from Québec spent 6 weeks in France and Switzerland to develop the contents and build the module on an e-learning Moodle platform under the supervision of two dermatopathologists. The learning module contains text, interactive clinical cases, tests with feedback, virtual slides, images and clinical photographs. For that module, the virtual slides are decentralized in 2 universities (Bordeaux and Paris 7). Each university is responsible of its own slide scanning, image storage and online display with virtual slide viewers. The module on inflammatory skin pathology includes more than 50 web pages with French original content, tests and clinical cases, links to over 45 virtual images and more than 50 microscopic and clinical photographs. The whole learning module is being revised by four dermatopathologists and two senior pathologists. It will be accessible to interns and residents in the spring of 2014. The experience and knowledge gained from that work will be transferred to the next international resident whose work will be aimed at creating lung and breast pathology learning modules. The challenges of sustaining a

  17. Online social network use by health care providers in a high traffic patient care environment.

    Science.gov (United States)

    Black, Erik; Light, Jennifer; Paradise Black, Nicole; Thompson, Lindsay

    2013-05-17

    The majority of workers, regardless of age or occupational status, report engaging in personal Internet use in the workplace. There is little understanding of the impact that personal Internet use may have on patient care in acute clinical settings. The objective of this study was to investigate the volume of one form of personal Internet use-online social networking (Facebook)-generated by workstations in the emergency department (ED) in contrast to measures of clinical volume and severity. The research team analyzed anonymous network utilization records for 68 workstations located in the emergency medicine department within one academic medical center for 15 consecutive days (12/29/2009 to 1/12/2010). This data was compared to ED work index (EDWIN) data derived by the hospital information systems. Health care workers spent an accumulated 4349 minutes (72.5 hours) browsing Facebook, staff cumulatively visited Facebook 9369 times and spent, on average, 12.0 minutes per hour browsing Facebook. There was a statistically significant difference in the time spent on Facebook according to time of day (19.8 minutes per hour versus 4.3 minutes per hour, P<.001). There was a significant, positive correlation between EDWIN scores and time spent on Facebook (r=.266, P<.001). Facebook use constituted a substantive percentage of staff time during the 15-day observation period. Facebook use increased with increased patient volume and severity within the ED.

  18. Online social networking addiction among college students in Singapore: Comorbidity with behavioral addiction and affective disorder.

    Science.gov (United States)

    Tang, Catherine So-Kum; Koh, Yvaine Yee Woen

    2017-02-01

    This study aimed to determine the prevalence of addiction to social networking sites/platforms (SNS) and its comorbidity with other behavioral addiction and affective disorder among college students in Singapore. 1110 college students (age: M=21.46, SD=1.80) in Singapore completed measures assessing online social networking, unhealthy food intake and shopping addiction as well as depression, anxiety and mania. Descriptive analyses were conducted to investigate the prevalence and comorbidity of behavioral addiction and affective disorder. Chi-square tests were used to examine gender differences. The prevalence rates of SNS, food and shopping addiction were 29.5%, 4.7% and 9.3% respectively for the total sample. SNS addiction was found to co-occur with food addiction (3%), shopping addiction (5%), and both food and shopping addiction (1%). The comorbidity rates of SNS addiction and affective disorder were 21% for depression, 27.7% for anxiety, and 26.1% for mania. Compared with the total sample, students with SNS addiction reported higher comorbidity rates with other behavioral addiction and affective disorder. In general, females as compared to males reported higher comorbidity rates of SNS addiction and affective disorder. SNS addiction has a high prevalence rate among college students in Singapore. Students with SNS addiction were vulnerable to experience other behavior addiction as well as affective disorder, especially among females. Copyright © 2016. Published by Elsevier B.V.

  19. Applying social network analysis to understand the knowledge sharing behaviour of practitioners in a clinical online discussion forum.

    Science.gov (United States)

    Stewart, Samuel Alan; Abidi, Syed Sibte Raza

    2012-12-04

    Knowledge Translation (KT) plays a vital role in the modern health care community, facilitating the incorporation of new evidence into practice. Web 2.0 tools provide a useful mechanism for establishing an online KT environment in which health practitioners share their practice-related knowledge and experiences with an online community of practice. We have implemented a Web 2.0 based KT environment--an online discussion forum--for pediatric pain practitioners across seven different hospitals in Thailand. The online discussion forum enabled the pediatric pain practitioners to share and translate their experiential knowledge to help improve the management of pediatric pain in hospitals. The goal of this research is to investigate the knowledge sharing dynamics of a community of practice through an online discussion forum. We evaluated the communication patterns of the community members using statistical and social network analysis methods in order to better understand how the online community engages to share experiential knowledge. Statistical analyses and visualizations provide a broad overview of the communication patterns within the discussion forum. Social network analysis provides the tools to delve deeper into the social network, identifying the most active members of the community, reporting the overall health of the social network, isolating the potential core members of the social network, and exploring the inter-group relationships that exist across institutions and professions. The statistical analyses revealed a network dominated by a single institution and a single profession, and found a varied relationship between reading and posting content to the discussion forum. The social network analysis discovered a healthy network with strong communication patterns, while identifying which users are at the center of the community in terms of facilitating communication. The group-level analysis suggests that there is strong interprofessional and interregional

  20. Dynamic evolving spiking neural networks for on-line spatio- and spectro-temporal pattern recognition.

    Science.gov (United States)

    Kasabov, Nikola; Dhoble, Kshitij; Nuntalid, Nuttapod; Indiveri, Giacomo

    2013-05-01

    On-line learning and recognition of spatio- and spectro-temporal data (SSTD) is a very challenging task and an important one for the future development of autonomous machine learning systems with broad applications. Models based on spiking neural networks (SNN) have already proved their potential in capturing spatial and temporal data. One class of them, the evolving SNN (eSNN), uses a one-pass rank-order learning mechanism and a strategy to evolve a new spiking neuron and new connections to learn new patterns from incoming data. So far these networks have been mainly used for fast image and speech frame-based recognition. Alternative spike-time learning methods, such as Spike-Timing Dependent Plasticity (STDP) and its variant Spike Driven Synaptic Plasticity (SDSP), can also be used to learn spatio-temporal representations, but they usually require many iterations in an unsupervised or semi-supervised mode of learning. This paper introduces a new class of eSNN, dynamic eSNN, that utilise both rank-order learning and dynamic synapses to learn SSTD in a fast, on-line mode. The paper also introduces a new model called deSNN, that utilises rank-order learning and SDSP spike-time learning in unsupervised, supervised, or semi-supervised modes. The SDSP learning is used to evolve dynamically the network changing connection weights that capture spatio-temporal spike data clusters both during training and during recall. The new deSNN model is first illustrated on simple examples and then applied on two case study applications: (1) moving object recognition using address-event representation (AER) with data collected using a silicon retina device; (2) EEG SSTD recognition for brain-computer interfaces. The deSNN models resulted in a superior performance in terms of accuracy and speed when compared with other SNN models that use either rank-order or STDP learning. The reason is that the deSNN makes use of both the information contained in the order of the first input spikes

  1. To friend or not to friend? Social networking and faculty perceptions of online professionalism.

    Science.gov (United States)

    Chretien, Katherine C; Farnan, Jeanne M; Greysen, S Ryan; Kind, Terry

    2011-12-01

    To assess faculty perceptions of professional boundaries and trainee-posted content on social networking sites (SNS). In June 2010, the Clerkship Directors in Internal Medicine conducted its annual survey of U.S. and Canadian member institutions. The survey included sections on demographics and social networking. The authors used descriptive statistics and tests of association to analyze the Likert scale responses and qualitatively analyzed the free-text responses. Of 110 institutional members, 82 (75%) responded to the survey. Of the 40 respondents who reported current or past SNS use, 21 (53%) reported receiving a "friend request" from a current student and 25 (63%) from a current resident. Of these, 4 (19%) accepted the student request and 12 (48%) accepted the resident request. Sixty-three of 80 (79%) felt it was inappropriate to send a friend request to a current student, 61 (76%) to accept a current student's request, 42 (53%) to become friends with a current resident, and 61 (81%) to become friends with a current patient. Becoming friends with a former student, former resident, or colleague was perceived as more appropriate. Younger respondents were less likely to deem specific student behaviors inappropriate (odds ratio [OR] 0.18-0.79; adjusted OR 0.12-0.86, controlling for respondents' sex, rank, and SNS use), although none reached statistical significance. Some internal medicine educators are using SNSs and interacting with trainees online. Their perceptions on the appropriateness of social networking behaviors provide some consensus for professional boundaries between faculty and trainees in the digital world.

  2. Sophisticated Online Learning Scheme for Green Resource Allocation in 5G Heterogeneous Cloud Radio Access Networks

    KAUST Repository

    Alqerm, Ismail

    2018-01-23

    5G is the upcoming evolution for the current cellular networks that aims at satisfying the future demand for data services. Heterogeneous cloud radio access networks (H-CRANs) are envisioned as a new trend of 5G that exploits the advantages of heterogeneous and cloud radio access networks to enhance spectral and energy efficiency. Remote radio heads (RRHs) are small cells utilized to provide high data rates for users with high quality of service (QoS) requirements, while high power macro base station (BS) is deployed for coverage maintenance and low QoS users service. Inter-tier interference between macro BSs and RRHs and energy efficiency are critical challenges that accompany resource allocation in H-CRANs. Therefore, we propose an efficient resource allocation scheme using online learning, which mitigates interference and maximizes energy efficiency while maintaining QoS requirements for all users. The resource allocation includes resource blocks (RBs) and power. The proposed scheme is implemented using two approaches: centralized, where the resource allocation is processed at a controller integrated with the baseband processing unit and decentralized, where macro BSs cooperate to achieve optimal resource allocation strategy. To foster the performance of such sophisticated scheme with a model free learning, we consider users\\' priority in RB allocation and compact state representation learning methodology to improve the speed of convergence and account for the curse of dimensionality during the learning process. The proposed scheme including both approaches is implemented using software defined radios testbed. The obtained results and simulation results confirm that the proposed resource allocation solution in H-CRANs increases the energy efficiency significantly and maintains users\\' QoS.

  3. Privacy Practices of Health Social Networking Sites: Implications for Privacy and Data Security in Online Cancer Communities.

    Science.gov (United States)

    Charbonneau, Deborah H

    2016-08-01

    While online communities for social support continue to grow, little is known about the state of privacy practices of health social networking sites. This article reports on a structured content analysis of privacy policies and disclosure practices for 25 online ovarian cancer communities. All of the health social networking sites in the study sample provided privacy statements to users, yet privacy practices varied considerably across the sites. The majority of sites informed users that personal information was collected about participants and shared with third parties (96%, n = 24). Furthermore, more than half of the sites (56%, n = 14) stated that cookies technology was used to track user behaviors. Despite these disclosures, only 36% (n = 9) offered opt-out choices for sharing data with third parties. In addition, very few of the sites (28%, n = 7) allowed individuals to delete their personal information. Discussions about specific security measures used to protect personal information were largely missing. Implications for privacy, confidentiality, consumer choice, and data safety in online environments are discussed. Overall, nurses and other health professionals can utilize these findings to encourage individuals seeking online support and participating in social networking sites to build awareness of privacy risks to better protect their personal health information in the digital age.

  4. Recruiting migrants for health research through social network sites: an online survey among chinese migrants in australia.

    Science.gov (United States)

    Hu, Jie; Wong, Kam Cheong; Wang, Zhiqiang

    2015-04-27

    Traditionally, postal surveys or face to face interviews are the main approaches for health researchers to obtain essential research data. However, with the prevalence of information technology and Internet, Web-based surveys are gaining popularity in health research. This study aims to report the process and outcomes of recruiting Chinese migrants through social network sites in Australia and to examine the sample characteristics of online recruitment by comparing the sample which was recruited by an online survey to a sample of Australian Chinese migrants collected by a postal survey. Descriptive analyses were performed to describe and compare the process and outcomes of online recruitment with postal survey questionnaires. Chi square tests and t tests were performed to assess the differences between the two samples for categorical and continuous variables respectively. In total, 473 Chinese migrants completed the online health survey from July to October 2013. Out of 426 participants recruited through the three Chinese social network sites in Australia, over 86.6% (369/426) were recruited within six weeks. Participants of the Web-based survey were younger, with a higher education level or had resided in Australia for less time compared to those recruited via a postal survey. However, there was no significant difference in gender, marital status, and professional occupation. The recruitment of Chinese migrants through social network sites in our online survey was feasible. Compared to a postal survey of Chinese migrants, the online survey attracted different group of Chinese migrants who may have diverse health needs and concerns. Our findings provided insightful information for researchers who are considering employing a Web-based approach to recruit migrants and ethnic minority participants.

  5. Online Social Network Users’ Attitudes toward Personality Traits Predict Behaviour of their Friends

    Directory of Open Access Journals (Sweden)

    Sergei A. Shchebetenko

    2016-12-01

    Full Text Available The research considers attitudes toward personality traits in online social network (OSN Vkontakte users’ behaviour. Users’ friends’ activity on a given user’s profile was supposed to be affected by attitudes toward traits of the latter. Within a broader context, the role of metacognitive type of characteristic adaptations as a key element of the five-factor theory of personality is studied. Accordingly, along with attitudes toward traits, other metacognitive characteristic adaptations are examined (e.g. dispositional efficiency, reflected trait, and reflected attitude toward a trait. 1030 undergraduates participated in the study. The research results confirm that extraversion is the most important predictor of OSN behavior among other personality traits. The information presented in this research is obtained using behavioural data instead of more convenient self-reports. Moreover, these behavioural data characterise other users’ (friends’ behaviour while addressing a certain user’s profile. Positive attitudes toward each Big Five traits (extraversion, agreeableness, conscientiousness, emotional stability, and openness to experience separately affected the number of “Likes” of the avatars representing users’ photographs. Furthermore, revealed correlations between traits and “Likes” were subsequently eliminated by the attitudes toward respective traits. Positive attitudes toward conscientiousness predicted the increase of friends’ number unlike trait conscientiousness. Positive attitude toward agreeableness predicted the increase of the number of posts written by friends on user’s wall unlike trait agreeableness. Attitudes toward traits are argued to affect social environment governed by an individual: one may select those social relationships and partners that fit better one’s attitudes toward traits. This, in turn, may affect actions of other people towards the given individual including those of online behaviour.

  6. Engineering online and in-person social networks to sustain physical activity: application of a conceptual model.

    Science.gov (United States)

    Rovniak, Liza S; Sallis, James F; Kraschnewski, Jennifer L; Sciamanna, Christopher N; Kiser, Elizabeth J; Ray, Chester A; Chinchilli, Vernon M; Ding, Ding; Matthews, Stephen A; Bopp, Melissa; George, Daniel R; Hovell, Melbourne F

    2013-08-14

    High rates of physical inactivity compromise the health status of populations globally. Social networks have been shown to influence physical activity (PA), but little is known about how best to engineer social networks to sustain PA. To improve procedures for building networks that shape PA as a normative behavior, there is a need for more specific hypotheses about how social variables influence PA. There is also a need to integrate concepts from network science with ecological concepts that often guide the design of in-person and electronically-mediated interventions. Therefore, this paper: (1) proposes a conceptual model that integrates principles from network science and ecology across in-person and electronically-mediated intervention modes; and (2) illustrates the application of this model to the design and evaluation of a social network intervention for PA. A conceptual model for engineering social networks was developed based on a scoping literature review of modifiable social influences on PA. The model guided the design of a cluster randomized controlled trial in which 308 sedentary adults were randomly assigned to three groups: WalkLink+: prompted and provided feedback on participants' online and in-person social-network interactions to expand networks for PA, plus provided evidence-based online walking program and weekly walking tips; WalkLink: evidence-based online walking program and weekly tips only; Minimal Treatment Control: weekly tips only. The effects of these treatment conditions were assessed at baseline, post-program, and 6-month follow-up. The primary outcome was accelerometer-measured PA. Secondary outcomes included objectively-measured aerobic fitness, body mass index, waist circumference, blood pressure, and neighborhood walkability; and self-reported measures of the physical environment, social network environment, and social network interactions. The differential effects of the three treatment conditions on primary and secondary

  7. Indigenous development and networking of online radon monitors in the underground uranium mine

    International Nuclear Information System (INIS)

    Gaware, J.J.; Sahoo, B.K.; Sapra, B.K.; Mayya, Y.S.

    2010-01-01

    Full text: There has been a long standing demand for online monitoring of radon level in various locations of underground uranium mine for taking care of radiological protection to workers. Nowadays, radon ( 222 Rn) monitors, based on semiconductor detector are increasingly employed for radon monitoring in environment. However, such instruments have some limitations such as (i) requirement of additional dryer in the sampling path, (ii) cannot be connected to a online data logging and monitoring network, (iii) not cost effective for large number of installations. Due to need for dryer, unattended continuous operation of such instruments is not possible particularly in underground uranium mine with humidity in the range of 80 to 98 %. So it is required to develop radon monitors which overcome the above limitations so that large number of monitors can be deployed in the uranium mine. Often radon progeny is electrostatically collected on the detector surface to increase the sensitivity. However, the collection efficiency is highly dependent upon the humidity and trace gas concentration in the sample gas due to charge neutralization effect. This effect can be minimized by applying a high electric field throughout the detector's chamber volume. This cannot be achieved using planner silicon PIN diode (area ∼ 4 cm 2 ) due to its inherent size limitations. This is because the electric field, in case of small inner electrode, falls off rapidly towards the outer electrode. Hence, an instrument has been indigenously developed by designing an annular cylindrical chamber with larger inner cathode (area = 140 cm 2 ) by employing flexible ZnS:Ag sheet (scintillation detector). With this design, the high sensitivity of 2.8 cph/Bqm -3 has been accomplished with the nominal deviation within 15% for vast change in humidity of 5% to 95%. In this instrument, although the alpha spectroscopy is not possible, the high sensitivity of the instruments makes it possible to achieve the MDL as

  8. Evaluating the feasibility of using online software to collect patient information in a chiropractic practice-based research network.

    Science.gov (United States)

    Kania-Richmond, Ania; Weeks, Laura; Scholten, Jeffrey; Reney, Mikaël

    2016-03-01

    Practice based research networks (PBRNs) are increasingly used as a tool for evidence based practice. We developed and tested the feasibility of using software to enable online collection of patient data within a chiropractic PBRN to support clinical decision making and research in participating clinics. To assess the feasibility of using online software to collect quality patient information. The study consisted of two phases: 1) Assessment of the quality of information provided, using a standardized form; and 2) Exploration of patients' perspectives and experiences regarding online information provision through semi-structured interviews. Data analysis was descriptive. Forty-five new patients were recruited. Thirty-six completed online forms, which were submitted by an appropriate person 100% of the time, with an error rate of less than 1%, and submitted in a timely manner 83% of the time. Twenty-one participants were interviewed. Overall, online forms were preferred given perceived security, ease of use, and enabling provision of more accurate information. Use of online software is feasible, provides high quality information, and is preferred by most participants. A pen-and-paper format should be available for patients with this preference and in case of technical difficulties.

  9. Scaling-Up Youth-Led Social Justice Efforts through an Online School-Based Social Network.

    Science.gov (United States)

    Kornbluh, Mariah; Neal, Jennifer Watling; Ozer, Emily J

    2016-06-01

    The exploration of social networking sites (SNS) in promoting social change efforts offers great potential within the field of community psychology. Online communities on SNS provide opportunities for bridging across groups, thus fostering the exchange of novel ideas and practices. Currently, there have only been limited efforts to examine SNS within the context of youth-led efforts. To explore the potential of SNS to facilitate the diffusion of social justice efforts between distinct youth groups, we linked three school-based youth-led participatory action research projects involving 54 high school students through a SNS. This study offers an innovative methodological approach and framework, utilizing social network analysis and strategic sampling of key student informants to investigate what individual behaviors and online network features predict student adoption of social change efforts. Findings highlight prospective facilitators and barriers to diffusion processes within a youth-led online network, as well as key constructs that may inform future research. We conclude by providing suggestions for scholars and practitioners interested in examining how SNS can be used to enhance the diffusion of social justice strategies, youth-led engagement efforts, and large-scale civic organizing. © Society for Community Research and Action 2016.

  10. Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks

    Directory of Open Access Journals (Sweden)

    Hesham Mostafa

    2017-09-01

    Full Text Available Artificial neural networks (ANNs trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the training phase, however, has attracted relatively little attention. In this paper, we describe a hardware-efficient on-line learning technique for feedforward multi-layer ANNs that is based on pipelined backpropagation. Learning is performed in parallel with inference in the forward pass, removing the need for an explicit backward pass and requiring no extra weight lookup. By using binary state variables in the feedforward network and ternary errors in truncated-error backpropagation, the need for any multiplications in the forward and backward passes is removed, and memory requirements for the pipelining are drastically reduced. Further reduction in addition operations owing to the sparsity in the forward neural and backpropagating error signal paths contributes to highly efficient hardware implementation. For proof-of-concept validation, we demonstrate on-line learning of MNIST handwritten digit classification on a Spartan 6 FPGA interfacing with an external 1Gb DDR2 DRAM, that shows small degradation in test error performance compared to an equivalently sized binary ANN trained off-line using standard back-propagation and exact errors. Our results highlight an attractive synergy between pipelined backpropagation and binary-state networks in substantially reducing computation and memory requirements, making pipelined on-line learning practical in deep networks.

  11. Hardware-Efficient On-line Learning through Pipelined Truncated-Error Backpropagation in Binary-State Networks.

    Science.gov (United States)

    Mostafa, Hesham; Pedroni, Bruno; Sheik, Sadique; Cauwenberghs, Gert

    2017-01-01

    Artificial neural networks (ANNs) trained using backpropagation are powerful learning architectures that have achieved state-of-the-art performance in various benchmarks. Significant effort has been devoted to developing custom silicon devices to accelerate inference in ANNs. Accelerating the training phase, however, has attracted relatively little attention. In this paper, we describe a hardware-efficient on-line learning technique for feedforward multi-layer ANNs that is based on pipelined backpropagation. Learning is performed in parallel with inference in the forward pass, removing the need for an explicit backward pass and requiring no extra weight lookup. By using binary state variables in the feedforward network and ternary errors in truncated-error backpropagation, the need for any multiplications in the forward and backward passes is removed, and memory requirements for the pipelining are drastically reduced. Further reduction in addition operations owing to the sparsity in the forward neural and backpropagating error signal paths contributes to highly efficient hardware implementation. For proof-of-concept validation, we demonstrate on-line learning of MNIST handwritten digit classification on a Spartan 6 FPGA interfacing with an external 1Gb DDR2 DRAM, that shows small degradation in test error performance compared to an equivalently sized binary ANN trained off-line using standard back-propagation and exact errors. Our results highlight an attractive synergy between pipelined backpropagation and binary-state networks in substantially reducing computation and memory requirements, making pipelined on-line learning practical in deep networks.

  12. Support or competition? How online social networks increase physical activity: A randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Jingwen Zhang, PhD

    2016-12-01

    Full Text Available To identify what features of online social networks can increase physical activity, we conducted a 4-arm randomized controlled trial in 2014 in Philadelphia, PA. Students (n = 790, mean age = 25.2 at an university were randomly assigned to one of four conditions composed of either supportive or competitive relationships and either with individual or team incentives for attending exercise classes. The social comparison condition placed participants into 6-person competitive networks with individual incentives. The social support condition placed participants into 6-person teams with team incentives. The combined condition with both supportive and competitive relationships placed participants into 6-person teams, where participants could compare their team's performance to 5 other teams' performances. The control condition only allowed participants to attend classes with individual incentives. Rewards were based on the total number of classes attended by an individual, or the average number of classes attended by the members of a team. The outcome was the number of classes that participants attended. Data were analyzed using multilevel models in 2014. The mean attendance numbers per week were 35.7, 38.5, 20.3, and 16.8 in the social comparison, the combined, the control, and the social support conditions. Attendance numbers were 90% higher in the social comparison and the combined conditions (mean = 1.9, SE = 0.2 in contrast to the two conditions without comparison (mean = 1.0, SE = 0.2 (p = 0.003. Social comparison was more effective for increasing physical activity than social support and its effects did not depend on individual or team incentives.

  13. Motives for Online Friending and Following: The Dark Side of Social Network Site Connections

    Directory of Open Access Journals (Sweden)

    Jaap W. Ouwerkerk

    2016-08-01

    Full Text Available Motives for “friending,” following, or connecting with others on social network sites are often positive, but darker motives may also play an important role. A survey with a novel Following Motives Scale (FMS demonstrates accordingly that positive, sociable motives (i.e., others providing a valued source for humor and information, others sharing a common background, as well as relationship maintenance and inspirational motives (i.e., others providing a target for upward social comparison can be distinguished from darker motives related to insecurity (i.e., others providing reassurance, preference for online interaction, mediated voyeurism, as well as social obligation, and even darker antisocial motives related to self-enhancement (i.e., others providing a target for downward social comparison, competition, schadenfreude, gossip, as well as “hate-following”. Results show that lower self-esteem and higher levels of need for popularity, narcissism, and dispositional schadenfreude characterize users with stronger dark side motives, whereas users with more sociable motives report more satisfaction with life, thereby providing construct validity for the novel scale. Convergent validity is demonstrated by positive relations between following motives and both time spent and following counts on different social network sites. Moreover, an embedded experiment shows that antisocial motives predicted acceptance of a Facebook friendship request from a male or female high school acquaintance who suffered a setback in the domain of appearance or status (i.e., a convenient source for self-enhancement, thereby providing additional convergent validity for the Antisocial Motives subscale.

  14. Predicting Social Networking Site Use and Online Communication Practices among Adolescents: The Role of Access and Device Ownership

    Directory of Open Access Journals (Sweden)

    Drew P. Cingel

    2014-01-01

    Full Text Available Given adolescents' heavy social media use, this study examined a number of predictors of adolescent social media use, as well as predictors of online communication practices. Using data collected from a national sample of 467 adolescents between the ages of 13 and 17, results indicate that demographics, technology access, and technology ownership are related to social media use and communication practices. Specifically, females log onto and use more constructive communication practices on Facebook compared to males. Additionally, adolescents who own smartphones engage in more constructive online communication practices than those who share regular cell phones or those who do not have access to a cell phone. Overall, results imply that ownership of mobile technologies, such as smartphones and iPads, may be more predictive of social networking site use and online communication practices than general ownership of technology.

  15. Predicting Social Networking Site Use and Online Communication Practices among Adolescents: The Role of Access and Device Ownership

    Directory of Open Access Journals (Sweden)

    Drew P. Cingel

    2014-06-01

    Full Text Available Given adolescents' heavy social media use, this study examined a number of predictors of adolescent social media use, as well as predictors of online communication practices. Using data collected from a national sample of 467 adolescents between the ages of 13 and 17, results indicate that demographics, technology access, and technology ownership are related to social media use and communication practices. Specifically, females log onto and use more constructive com-munication practices on Facebook compared to males. Additionally, adolescents who own smartphones engage in more constructive online communication practices than those who share regular cell phones or those who do not have access to a cell phone. Overall, results imply that ownership of mobile technologies, such as smartphones and iPads, may be more predictive of social networking site use and online communication practices than general ownership of technology.

  16. Romantic Partner Monitoring After Breakups: Attachment, Dependence, Distress, and Post-Dissolution Online Surveillance via Social Networking Sites.

    Science.gov (United States)

    Fox, Jesse; Tokunaga, Robert S

    2015-09-01

    Romantic relationship dissolution can be stressful, and social networking sites make it difficult to separate from a romantic partner online as well as offline. An online survey (N = 431) tested a model synthesizing attachment, investment model variables, and post-dissolution emotional distress as predictors of interpersonal surveillance (i.e., "Facebook stalking") of one's ex-partner on Facebook after a breakup. Results indicated that anxious attachment predicted relational investment but also seeking relationship alternatives; avoidant attachment was negatively related to investment but positively related to seeking alternatives. Investment predicted commitment, whereas seeking alternatives was negatively related to commitment. Commitment predicted emotional distress after the breakup. Distress predicted partner monitoring immediately following the breakup, particularly for those who did not initiate the breakup, as well as current partner monitoring. Given their affordances, social media are discussed as potentially unhealthy enablers for online surveillance after relationship termination.

  17. Identity Confusion and Materialism Mediate the Relationship Between Excessive Social Network Site Usage and Online Compulsive Buying.

    Science.gov (United States)

    Sharif, Saeed Pahlevan; Khanekharab, Jasmine

    2017-08-01

    This study investigates the mediating role of identity confusion and materialism in the relationship between social networking site (SNS) excessive usage and online compulsive buying among young adults. A total of 501 SNS users aged 17 to 23 years (M = 19.68, SD = 1.65) completed an online survey questionnaire. A serial multiple mediator model was developed and hypotheses were tested using structural equation modeling. The results showed that excessive young adult SNS users had a higher tendency toward compulsive buying online. This was partly because they experienced higher identity confusion and developed higher levels of materialism. Targeted psychological interventions seeking to gradually increase identity clarity to buffer the detrimental effects of SNS usage and identity confusion in young adults are suggested.

  18. Health Social Networks as Online Life Support Groups for Patients With Cardiovascular Diseases

    International Nuclear Information System (INIS)

    Medina, Edhelmira Lima; Loques, Orlando Filho; Mesquita, Cláudio Tinoco

    2013-01-01

    The number of patients who use the internet in search for information that might improve their health conditions has increased. Among them, those looking for virtual environments to share experiences, doubts, opinions, and emotions, and to foster relationships aimed at giving and getting support stand out. Therefore, there is an increasing need to assess how those environments can affect the patients' health. This study was aimed at identifying scientific studies on the proliferation and impact of virtual communities, known as health social networks or online support groups, directed to cardiovascular diseases, which might be useful to patients with certain conditions, providing them with information and emotional support. A systematic review of the literature was conducted with articles published from 2007 to 2012, related to cardiovascular diseases and collected from the following databases: PubMed; Association for Computing Machinery(ACM); and Institute of Electrical and Electronics Engineers (IEEE). Four articles meeting the inclusion criteria were selected. The results were interesting and relevant from the health viewpoint, identifying therapeutic benefits, such as provision of emotional support, greater compliance to treatment, and information sharing on diseases and on life experiences

  19. The Influence of Culture on the Expression of Emotions in Online Social Networks

    Directory of Open Access Journals (Sweden)

    Cathia PAPI

    2016-12-01

    Full Text Available Seeking to understand the influence of culture on the expression of emotions in online social networks, we analyzed four Facebook groups – two from Quebec, Canada and two from Colombia – created following unexpected deaths. Comparison of the messages posted in these groups reveals a stronger tendency to maintain a virtual relationship with the deceased by Canadians than by Columbians. Among the former, the deceased is more often asked to and thanked for watching over the living, and testimonies of love addressed to the deceased are more numerous than among the latter. Among the latter, the strength of the links maintained with the deceased justifying the present pain and evocation of the mourners’ Catholic beliefs are relatively more frequent. Finally, while the Canadian Quebecers’ messages would presumably be written in French and those of Colombians in Spanish, it is interesting to observe a certain presence of English to express feelings of loss and love in the four groups, as well as a certain affinity between North American virtual bereavement practices and those seemingly more characteristic of women, the main contributors in all four groups.

  20. Assessment of erosion and sedimentation dynamic in a combined sewer network using online turbidity monitoring.

    Science.gov (United States)

    Bersinger, T; Le Hécho, I; Bareille, G; Pigot, T

    2015-01-01

    Eroded sewer sediments are a significant source of organic matter discharge by combined sewer overflows. Many authors have studied the erosion and sedimentation processes at the scale of a section of sewer pipe and over short time periods. The objective of this study was to assess these processes at the scale of an entire sewer network and over 1 month, to understand whether phenomena observed on a small scale of space and time are still valid on a larger scale. To achieve this objective the continuous monitoring of turbidity was used. First, the study of successive rain events allows observation of the reduction of the available sediment and highlights the widely different erosion resistance for the different sediment layers. Secondly, calculation of daily chemical oxygen demand (COD) fluxes during the entire month was performed showing that sediment storage in the sewer pipe after a rain period is important and stops after 5 days. Nevertheless, during rainfall events, the eroded fluxes are more important than the whole sewer sediment accumulated during a dry weather period. This means that the COD fluxes promoted by runoff are substantial. This work confirms, with online monitoring, most of the conclusions from other studies on a smaller scale.

  1. Trust-Based Access Control Model from Sociological Approach in Dynamic Online Social Network Environment

    Science.gov (United States)

    Kim, Seungjoo

    2014-01-01

    There has been an explosive increase in the population of the OSN (online social network) in recent years. The OSN provides users with many opportunities to communicate among friends and family. Further, it facilitates developing new relationships with previously unknown people having similar beliefs or interests. However, the OSN can expose users to adverse effects such as privacy breaches, the disclosing of uncontrolled material, and the disseminating of false information. Traditional access control models such as MAC, DAC, and RBAC are applied to the OSN to address these problems. However, these models are not suitable for the dynamic OSN environment because user behavior in the OSN is unpredictable and static access control imposes a burden on the users to change the access control rules individually. We propose a dynamic trust-based access control for the OSN to address the problems of the traditional static access control. Moreover, we provide novel criteria to evaluate trust factors such as sociological approach and evaluate a method to calculate the dynamic trust values. The proposed method can monitor negative behavior and modify access permission levels dynamically to prevent the indiscriminate disclosure of information. PMID:25374943

  2. Trust-Based Access Control Model from Sociological Approach in Dynamic Online Social Network Environment

    Directory of Open Access Journals (Sweden)

    Seungsoo Baek

    2014-01-01

    Full Text Available There has been an explosive increase in the population of the OSN (online social network in recent years. The OSN provides users with many opportunities to communicate among friends and family. Further, it facilitates developing new relationships with previously unknown people having similar beliefs or interests. However, the OSN can expose users to adverse effects such as privacy breaches, the disclosing of uncontrolled material, and the disseminating of false information. Traditional access control models such as MAC, DAC, and RBAC are applied to the OSN to address these problems. However, these models are not suitable for the dynamic OSN environment because user behavior in the OSN is unpredictable and static access control imposes a burden on the users to change the access control rules individually. We propose a dynamic trust-based access control for the OSN to address the problems of the traditional static access control. Moreover, we provide novel criteria to evaluate trust factors such as sociological approach and evaluate a method to calculate the dynamic trust values. The proposed method can monitor negative behavior and modify access permission levels dynamically to prevent the indiscriminate disclosure of information.

  3. Health Social Networks as Online Life Support Groups for Patients With Cardiovascular Diseases

    Energy Technology Data Exchange (ETDEWEB)

    Medina, Edhelmira Lima, E-mail: edhyly@ic.uff.br; Loques, Orlando Filho [Instituto de Computação - Universidade Federal Fluminense, Niterói, RJ (Brazil); Mesquita, Cláudio Tinoco [Hospital Universitário Antônio Pedro - Universidade Federal Fluminense, Niterói, RJ (Brazil)

    2013-08-15

    The number of patients who use the internet in search for information that might improve their health conditions has increased. Among them, those looking for virtual environments to share experiences, doubts, opinions, and emotions, and to foster relationships aimed at giving and getting support stand out. Therefore, there is an increasing need to assess how those environments can affect the patients' health. This study was aimed at identifying scientific studies on the proliferation and impact of virtual communities, known as health social networks or online support groups, directed to cardiovascular diseases, which might be useful to patients with certain conditions, providing them with information and emotional support. A systematic review of the literature was conducted with articles published from 2007 to 2012, related to cardiovascular diseases and collected from the following databases: PubMed; Association for Computing Machinery(ACM); and Institute of Electrical and Electronics Engineers (IEEE). Four articles meeting the inclusion criteria were selected. The results were interesting and relevant from the health viewpoint, identifying therapeutic benefits, such as provision of emotional support, greater compliance to treatment, and information sharing on diseases and on life experiences.

  4. User Profile Analysis Using an Online Social Network Integrated Quiz Game

    Directory of Open Access Journals (Sweden)

    Yusuf YASLAN

    2017-09-01

    Full Text Available User interest profiling is important for personalized web search, recommendation and retrieval systems. In order to develop a good personalized application one needs to have accurate representation of user profiles. Most of the personalized systems generate interest profiles from user declarations or inferred from cookies or visited web pages. But to achieve a certain result that satisfies the user needs, explicit definition of the user interests is needed. In this paper we propose to obtain interest profiles from a quiz game played by the user where at each play he/she is asked 10 questions from different categories with different difficulty levels. The developed quiz game is integrated to Facebook online social network. By doing so, we had the chance to extract each user’s both explicit Facebook interest profiles and implicit interest profiles from quiz game answers. These profiles are used to extract different features for each user. Both implicit interest profile and explicit interest profile features are evaluated for clustering and interest ranking tasks separately. The experimental results show that the implicit interest profile features have promising results on personalized systems.

  5. The development and feasibility of an online aphasia group intervention and networking program - TeleGAIN.

    Science.gov (United States)

    Pitt, Rachelle; Theodoros, Deborah; Hill, Anne J; Russell, Trevor

    2017-09-04

    Aphasia group therapy offers many benefits, however people with aphasia report difficulty accessing groups and speech-language pathologists are faced with many challenges in providing aphasia group therapy. Telerehabilitation may offer an alternative service delivery option. An online aphasia group therapy program - Telerehabilitation Group Aphasia Intervention and Networking (TeleGAIN) - has been developed according to the guidelines of the Medical Research Council (MRC) framework for complex interventions. The purpose of this paper is to describe the development of TeleGAIN and the results of a pilot trial to determine feasibility and acceptability. The development of TeleGAIN was informed through literature reviews in relevant topic areas, consideration of expert opinion and application of the social cognitive theory. TeleGAIN was then modelled through a feasibility pilot trial with four people with aphasia. TeleGAIN appeared to be feasible and acceptable to participants and able to be implemented as planned. Participant satisfaction with treatment was high and results suggested some potential for improvements in language functioning and communication-related quality of life. TeleGAIN appeared to be feasible and acceptable, however the study highlighted issues related to technology, clinical implementation and participant-specific factors that should be addressed prior to a larger trial.

  6. Associative memory for online learning in noisy environments using self-organizing incremental neural network.

    Science.gov (United States)

    Sudo, Akihito; Sato, Akihiro; Hasegawa, Osamu

    2009-06-01

    Associative memory operating in a real environment must perform well in online incremental learning and be robust to noisy data because noisy associative patterns are presented sequentially in a real environment. We propose a novel associative memory that satisfies these requirements. Using the proposed method, new associative pairs that are presented sequentially can be learned accurately without forgetting previously learned patterns. The memory size of the proposed method increases adaptively with learning patterns. Therefore, it suffers neither redundancy nor insufficiency of memory size, even in an environment in which the maximum number of associative pairs to be presented is unknown before learning. Noisy inputs in real environments are classifiable into two types: noise-added original patterns and faultily presented random patterns. The proposed method deals with two types of noise. To our knowledge, no conventional associative memory addresses noise of both types. The proposed associative memory performs as a bidirectional one-to-many or many-to-one associative memory and deals not only with bipolar data, but also with real-valued data. Results demonstrate that the proposed method's features are important for application to an intelligent robot operating in a real environment. The originality of our work consists of two points: employing a growing self-organizing network for an associative memory, and discussing what features are necessary for an associative memory for an intelligent robot and proposing an associative memory that satisfies those requirements.

  7. Unsupervised Scalable Statistical Method for Identifying Influential Users in Online Social Networks.

    Science.gov (United States)

    Azcorra, A; Chiroque, L F; Cuevas, R; Fernández Anta, A; Laniado, H; Lillo, R E; Romo, J; Sguera, C

    2018-05-03

    Billions of users interact intensively every day via Online Social Networks (OSNs) such as Facebook, Twitter, or Google+. This makes OSNs an invaluable source of information, and channel of actuation, for sectors like advertising, marketing, or politics. To get the most of OSNs, analysts need to identify influential users that can be leveraged for promoting products, distributing messages, or improving the image of companies. In this report we propose a new unsupervised method, Massive Unsupervised Outlier Detection (MUOD), based on outliers detection, for providing support in the identification of influential users. MUOD is scalable, and can hence be used in large OSNs. Moreover, it labels the outliers as of shape, magnitude, or amplitude, depending of their features. This allows classifying the outlier users in multiple different classes, which are likely to include different types of influential users. Applying MUOD to a subset of roughly 400 million Google+ users, it has allowed identifying and discriminating automatically sets of outlier users, which present features associated to different definitions of influential users, like capacity to attract engagement, capacity to attract a large number of followers, or high infection capacity.

  8. "Supporting Early Career Women in the Geosciences through Online Peer-Mentoring: Lessons from the Earth Science Women's Network (ESWN)"

    Science.gov (United States)

    Holloway, T.; Hastings, M. G.; Barnes, R. T.; Fischer, E. V.; Wiedinmyer, C.; Rodriguez, C.; Adams, M. S.; Marin-Spiotta, E.

    2014-12-01

    The Earth Science Women's Network (ESWN) is an international peer-mentoring organization with over 2000 members, dedicated to career development and community for women across the geosciences. Since its formation in 2002, ESWN has supported the growth of a more diverse scientific community through a combination of online and in-person networking activities. Lessons learned related to online networking and community-building will be presented. ESWN serves upper-level undergraduates, graduate students, professionals in a range of environmental fields, scientists working in federal and state governments, post-doctoral researchers, and academic faculty and scientists. Membership includes women working in over 50 countries, although the majority of ESWN members work in the U.S. ESWN increases retention of women in the geosciences by enabling and supporting professional person-to-person connections. This approach has been shown to reduce feelings of isolation among our members and help build professional support systems critical to career success. In early 2013 ESWN transitioned online activities to an advanced social networking platform that supports discussion threads, group formation, and individual messaging. Prior to that, on-line activities operated through a traditional list-serve, hosted by the National Center for Atmospheric Research (NCAR). The new web center, http://eswnonline.org, serves as the primary forum for members to build connections, seek advice, and share resources. For example, members share job announcements, discuss issues of work-life balance, and organize events at professional conferences. ESWN provides a platform for problem-based mentoring, drawing from the wisdom of colleagues across a range of career stages.

  9. Effects of Electronic Trust on Purchase Intentions in Online Social Review Networks: The Case of Tripadvisor.com

    OpenAIRE

    Öztüren, Ali

    2013-01-01

    The purpose of this research study is to examine the effects of trust beliefs on purchase intentions of trip planners within the context of online social review network by analyzing dimensions of e-trust and effects on purchase intentions. With the intention to test these effects a survey was executed and the data collected from 320 participants. Multiple regression analysis was conducted to analyze the hypotheses related to the factors affecting the overall electronic trust level and purchas...

  10. PREDICTIVE CONTROL OF A BATCH POLYMERIZATION SYSTEM USING A FEEDFORWARD NEURAL NETWORK WITH ONLINE ADAPTATION BY GENETIC ALGORITHM

    Directory of Open Access Journals (Sweden)

    A. Cancelier

    Full Text Available Abstract This study used a predictive controller based on an empirical nonlinear model comprising a three-layer feedforward neural network for temperature control of the suspension polymerization process. In addition to the offline training technique, an algorithm was also analyzed for online adaptation of its parameters. For the offline training, the network was statically trained and the genetic algorithm technique was used in combination with the least squares method. For online training, the network was trained on a recurring basis and only the technique of genetic algorithms was used. In this case, only the weights and bias of the output layer neuron were modified, starting from the parameters obtained from the offline training. From the experimental results obtained in a pilot plant, a good performance was observed for the proposed control system, with superior performance for the control algorithm with online adaptation of the model, particularly with respect to the presence of off-set for the case of the fixed parameters model.

  11. A General Bayesian Network Approach to Analyzing Online Game Item Values and Its Influence on Consumer Satisfaction and Purchase Intention

    Science.gov (United States)

    Lee, Kun Chang; Park, Bong-Won

    Many online game users purchase game items with which to play free-to-play games. Because of a lack of research into which there is no specified framework for categorizing the values of game items, this study proposes four types of online game item values based on an analysis of literature regarding online game characteristics. It then proposes to investigate how online game users perceive satisfaction and purchase intention from the proposed four types of online game item values. Though regression analysis has been used frequently to answer this kind of research question, we propose a new approach, a General Bayesian Network (GBN), which can be performed in an understandable way without sacrificing predictive accuracy. Conventional techniques, such as regression analysis, do not provide significant explanation for this kind of problem because they are fixed to a linear structure and are limited in explaining why customers are likely to purchase game items and if they are satisfied with their purchases. In contrast, the proposed GBN provides a flexible underlying structure based on questionnaire survey data and offers robust decision support on this kind of research question by identifying its causal relationships. To illustrate the validity of GBN in solving the research question in this study, 327 valid questionnaires were analyzed using GBN with what-if and goal-seeking approaches. The experimental results were promising and meaningful in comparison with regression analysis results.

  12. Neural network based online simultaneous policy update algorithm for solving the HJI equation in nonlinear H∞ control.

    Science.gov (United States)

    Wu, Huai-Ning; Luo, Biao

    2012-12-01

    It is well known that the nonlinear H∞ state feedback control problem relies on the solution of the Hamilton-Jacobi-Isaacs (HJI) equation, which is a nonlinear partial differential equation that has proven to be impossible to solve analytically. In this paper, a neural network (NN)-based online simultaneous policy update algorithm (SPUA) is developed to solve the HJI equation, in which knowledge of internal system dynamics is not required. First, we propose an online SPUA which can be viewed as a reinforcement learning technique for two players to learn their optimal actions in an unknown environment. The proposed online SPUA updates control and disturbance policies simultaneously; thus, only one iterative loop is needed. Second, the convergence of the online SPUA is established by proving that it is mathematically equivalent to Newton's method for finding a fixed point in a Banach space. Third, we develop an actor-critic structure for the implementation of the online SPUA, in which only one critic NN is needed for approximating the cost function, and a least-square method is given for estimating the NN weight parameters. Finally, simulation studies are provided to demonstrate the effectiveness of the proposed algorithm.

  13. Online support for transgender people: an analysis of forums and social networks.

    Science.gov (United States)

    Cipolletta, Sabrina; Votadoro, Riccardo; Faccio, Elena

    2017-09-01

    Transgender people face a range of personal and social conflicts that strongly influence their well-being. In many cases, the Internet can become the main resource in terms of finding support. The aim of this study was to understand how transgender people give and receive help online. Between 2013 and 2015, 122 online community conversations were collected on Italian forums and Facebook groups involving transgender people, and online interviews were conducted with 16 users of these communities. A qualitative content analysis was conducted by using the software package, NVivo10. The main categories that emerged were: motivations to join an online community, online help, differences between online and offline interactions, status, conflicts and professional help. Results indicate that participation in online communities often derives from the users' need for help. This help can be given by peers who have had similar experiences, and by professionals who participate in the discussions as moderator. The need to test one's own identity, to compare oneself with others and to share one's personal experiences made online communities at risk of exposing users to invalidation and transphobic messages. Administrators and moderators try to ensure the safety of users, and suggest that they ask for professional help offline and/or online when over-specific medical advice was sought. This study confirms that transgender people might find benefit from an online platform of help and support and might minimise distance problems, increase financial convenience and foster disinhibition. © 2017 John Wiley & Sons Ltd.

  14. The Impact of Online Social Networks on Health and Health Systems: A Scoping Review and Case Studies.

    Science.gov (United States)

    Griffiths, Frances; Dobermann, Tim; Cave, Jonathan A K; Thorogood, Margaret; Johnson, Samantha; Salamatian, Kavé; Gomez Olive, Francis X; Goudge, Jane

    2015-12-01

    Interaction through online social networks potentially results in the contestation of prevailing ideas about health and health care, and to mass protest where health is put at risk or health care provision is wanting. Through a review of the academic literature and case studies of four social networking health sites (PatientsLikeMe, Mumsnet, Treatment Action Campaign, and My Pro Ana), we establish the extent to which this phenomenon is documented, seek evidence of the prevalence and character of health-related networks, and explore their structure, function, participants, and impact, seeking to understand how they came into being and how they sustain themselves. Results indicate mass protest is not arising from these established health-related networking platforms. There is evidence of changes in policy following campaigning activity prompted by experiences shared through social networking such as improved National Health Service care for miscarriage (a Mumsnet campaign). Platform owners and managers have considerable power to shape these campaigns. Social networking is also influencing health policy indirectly through increasing awareness and so demand for health care. Transient social networking about health on platforms such as Twitter were not included as case studies but may be where the most radical or destabilizing influence on health care policy might arise.

  15. A Qualitative Study to Examine Feasibility and Design of an Online Social Networking Intervention to Increase Physical Activity in Teenage Girls.

    Science.gov (United States)

    Van Kessel, Gisela; Kavanagh, Madeleine; Maher, Carol

    2016-01-01

    Online social networks present wide-reaching and flexible platforms through which to deliver health interventions to targeted populations. This study used a social marketing approach to explore teenage girls' perceptions of physical activity and the potential use of online social networks to receive a physical activity intervention. Six focus groups were conducted with 19 Australian teenage girls (ages 13 to 18 years) with varying levels of physical activity and socioeconomic status. A semi-structured format was used, with groups discussion transcribed verbatim. Content analysis identified emergent themes, with triangulation and memos used to ensure accuracy. Physical activity was most appealing when it emphasised sport, exercise and fitness, along with opportunities for socialisation with friends and self-improvement. Participants were receptive to delivery of a physical activity intervention via online social networks, with Facebook the most widely reported site. Participants commonly accessed online social networks via mobile devices and particularly smartphones. Undesirable features included promotion of physical activity in terms of walking; use of cartoon imagery; use of humour; and promotion of the intervention via schools, each of which were considered "uncool". Participants noted that their parents were likely to be supportive of them using an online social networking physical activity intervention, particularly if not promoted as a weight loss intervention. This study identified key features likely to increase the feasibility and retention of an online social networking physical activity intervention for teenage girls. Guidelines for the design of interventions for teenage girls are provided for future applications.

  16. A Qualitative Study to Examine Feasibility and Design of an Online Social Networking Intervention to Increase Physical Activity in Teenage Girls.

    Directory of Open Access Journals (Sweden)

    Gisela Van Kessel

    Full Text Available Online social networks present wide-reaching and flexible platforms through which to deliver health interventions to targeted populations. This study used a social marketing approach to explore teenage girls' perceptions of physical activity and the potential use of online social networks to receive a physical activity intervention.Six focus groups were conducted with 19 Australian teenage girls (ages 13 to 18 years with varying levels of physical activity and socioeconomic status. A semi-structured format was used, with groups discussion transcribed verbatim. Content analysis identified emergent themes, with triangulation and memos used to ensure accuracy.Physical activity was most appealing when it emphasised sport, exercise and fitness, along with opportunities for socialisation with friends and self-improvement. Participants were receptive to delivery of a physical activity intervention via online social networks, with Facebook the most widely reported site. Participants commonly accessed online social networks via mobile devices and particularly smartphones. Undesirable features included promotion of physical activity in terms of walking; use of cartoon imagery; use of humour; and promotion of the intervention via schools, each of which were considered "uncool". Participants noted that their parents were likely to be supportive of them using an online social networking physical activity intervention, particularly if not promoted as a weight loss intervention.This study identified key features likely to increase the feasibility and retention of an online social networking physical activity intervention for teenage girls. Guidelines for the design of interventions for teenage girls are provided for future applications.

  17. Dynamic neural networks based on-line identification and control of high performance motor drives

    Science.gov (United States)

    Rubaai, Ahmed; Kotaru, Raj

    1995-01-01

    In the automated and high-tech industries of the future, there wil be a need for high performance motor drives both in the low-power range and in the high-power range. To meet very straight demands of tracking and regulation in the two quadrants of operation, advanced control technologies are of a considerable interest and need to be developed. In response a dynamics learning control architecture is developed with simultaneous on-line identification and control. the feature of the proposed approach, to efficiently combine the dual task of system identification (learning) and adaptive control of nonlinear motor drives into a single operation is presented. This approach, therefore, not only adapts to uncertainties of the dynamic parameters of the motor drives but also learns about their inherent nonlinearities. In fact, most of the neural networks based adaptive control approaches in use have an identification phase entirely separate from the control phase. Because these approaches separate the identification and control modes, it is not possible to cope with dynamic changes in a controlled process. Extensive simulation studies have been conducted and good performance was observed. The robustness characteristics of neuro-controllers to perform efficiently in a noisy environment is also demonstrated. With this initial success, the principal investigator believes that the proposed approach with the suggested neural structure can be used successfully for the control of high performance motor drives. Two identification and control topologies based on the model reference adaptive control technique are used in this present analysis. No prior knowledge of load dynamics is assumed in either topology while the second topology also assumes no knowledge of the motor parameters.

  18. Online social networking by patients with diabetes: a qualitative evaluation of communication with Facebook.

    Science.gov (United States)

    Greene, Jeremy A; Choudhry, Niteesh K; Kilabuk, Elaine; Shrank, William H

    2011-03-01

    Several disease-specific information exchanges now exist on Facebook and other online social networking sites. These new sources of knowledge, support, and engagement have become important for patients living with chronic disease, yet the quality and content of the information provided in these digital arenas are poorly understood. To qualitatively evaluate the content of communication in Facebook communities dedicated to diabetes. We identified the 15 largest Facebook groups focused on diabetes management. For each group, we downloaded the 15 most recent "wall posts" and the 15 most recent discussion topics from the 10 largest groups. Four hundred eighty unique users were identified in a series of 690 comments from wall posts and discussion topics. Posts were abstracted and aggregated into a database. Two investigators evaluated the posts, developed a thematic coding scheme, and applied codes to the data. Patients with diabetes, family members, and their friends use Facebook to share personal clinical information, to request disease-specific guidance and feedback, and to receive emotional support. Approximately two-thirds of posts included unsolicited sharing of diabetes management strategies, over 13% of posts provided specific feedback to information requested by other users, and almost 29% of posts featured an effort by the poster to provide emotional support to others as members of a community. Approximately 27% of posts featured some type of promotional activity, generally presented as testimonials advertising non-FDA approved, "natural" products. Clinically inaccurate recommendations were infrequent, but were usually associated with promotion of a specific product or service. Thirteen percent of posts contained requests for personal information from Facebook participants. Facebook provides a forum for reporting personal experiences, asking questions, and receiving direct feedback for people living with diabetes. However, promotional activity and personal

  19. Online social networking and US poison control centers: Facebook as a means of information distribution.

    Science.gov (United States)

    Vo, Kathy; Smollin, Craig

    2015-06-01

    Online social networking services such as Facebook provide a novel medium for the dissemination of public health information by poison control centers in the United States. We performed a cross-sectional study of poison control center Facebook pages to describe and assess the use of this medium. Facebook pages associated with poison control centers were identified during a continuous two-week period from December 24, 2012 to January 7, 2013. Data were extracted from each page, including affiliated poison control center; page duration, measured in years since registration; number of subscribers; number of postings by general toxicological category; and measures of user-generated activity including "likes", "shares", and comments per posting. Among the 56 US poison control centers, 39 Facebook pages were identified, of which 29 were currently active. The total number of active pages has increased by 140% from 2009 to 2013 (average of 25% per year). The total number of all subscribers to active pages was 11,211, ranging from 40 to 2,456 (mean 387, SD 523), equal to 0.006% of all Facebook users in the United States. The number of subscribers per page was associated with page duration, number of postings, and type of postings. The types of toxicological postings were public education (45%), self-promotion (28%), childhood safety (12%), drugs of abuse (8%), environmental poisonings (6%), and general overdoses (1%). Slightly over half of all poison control centers in the United States are supplementing their outreach and education efforts through Facebook. In general, the more active the poison control center on Facebook, the more page followers and follower engagement gained.

  20. How social network analysis can be used to monitor online collaborative learning and guide an informed intervention.

    Science.gov (United States)

    Saqr, Mohammed; Fors, Uno; Tedre, Matti; Nouri, Jalal

    2018-01-01

    To ensure online collaborative learning meets the intended pedagogical goals (is actually collaborative and stimulates learning), mechanisms are needed for monitoring the efficiency of online collaboration. Various studies have indicated that social network analysis can be particularly effective in studying students' interactions in online collaboration. However, research in education has only focused on the theoretical potential of using SNA, not on the actual benefits they achieved. This study investigated how social network analysis can be used to monitor online collaborative learning, find aspects in need of improvement, guide an informed intervention, and assess the efficacy of intervention using an experimental, observational repeated-measurement design in three courses over a full-term duration. Using a combination of SNA-based visual and quantitative analysis, we monitored three SNA constructs for each participant: the level of interactivity, the role, and position in information exchange, and the role played by each participant in the collaboration. On the group level, we monitored interactivity and group cohesion indicators. Our monitoring uncovered a non-collaborative teacher-centered pattern of interactions in the three studied courses as well as very few interactions among students, limited information exchange or negotiation, and very limited student networks dominated by the teacher. An intervention based on SNA-generated insights was designed. The intervention was structured into five actions: increasing awareness, promoting collaboration, improving the content, preparing teachers, and finally practicing with feedback. Evaluation of the intervention revealed that it has significantly enhanced student-student interactions and teacher-student interactions, as well as produced a collaborative pattern of interactions among most students and teachers. Since efficient and communicative activities are essential prerequisites for successful content

  1. "Everybody Puts Their Whole Life on Facebook": Identity Management and the Online Social Networks of LGBTQ Youth.

    Science.gov (United States)

    McConnell, Elizabeth; Néray, Bálint; Hogan, Bernie; Korpak, Aaron; Clifford, Antonia; Birkett, Michelle

    2018-05-26

    Lesbian, gay, bisexual, transgender, and queer (LGBTQ) youth and young adults almost inevitably "come out", or self-disclose their identity to others. Some LGBTQ youth are more uniformly "out", while others may disclose to some groups but not others. This selective disclosure is complicated on real name social media sites, which tend to encourage a unified presentation of self across social contexts. We explore these complications with a cohort of LBGTQ youth on Facebook ( N = 199, M age = 24.13). Herein we ask: How do LBGTQ youth manage the disclosure of their sexual orientation and/or gender identity to different people in their lives? Further, are there identifiable differences in the online social network structure for LGBTQ youth who manage outness in different ways? Finally, how do LGBTQ young people describe their experiences on Facebook? We answer these questions using a mixed methods approach, combining statistical cluster analysis, network visualization, and qualitative data. Our findings illustrate patterns in network structure by outness cluster type, highlighting both the work involved in managing one's online identity as well as the costs to (semi-) closeted individuals including a considerably lower overall network connectivity. In particular, outness to family characterized LGBTQ young people's experiences on Facebook.

  2. “Everybody Puts Their Whole Life on Facebook”: Identity Management and the Online Social Networks of LGBTQ Youth

    Directory of Open Access Journals (Sweden)

    Elizabeth McConnell

    2018-05-01

    Full Text Available Lesbian, gay, bisexual, transgender, and queer (LGBTQ youth and young adults almost inevitably “come out”, or self-disclose their identity to others. Some LGBTQ youth are more uniformly “out”, while others may disclose to some groups but not others. This selective disclosure is complicated on real name social media sites, which tend to encourage a unified presentation of self across social contexts. We explore these complications with a cohort of LBGTQ youth on Facebook (N = 199, Mage = 24.13. Herein we ask: How do LBGTQ youth manage the disclosure of their sexual orientation and/or gender identity to different people in their lives? Further, are there identifiable differences in the online social network structure for LGBTQ youth who manage outness in different ways? Finally, how do LGBTQ young people describe their experiences on Facebook? We answer these questions using a mixed methods approach, combining statistical cluster analysis, network visualization, and qualitative data. Our findings illustrate patterns in network structure by outness cluster type, highlighting both the work involved in managing one’s online identity as well as the costs to (semi- closeted individuals including a considerably lower overall network connectivity. In particular, outness to family characterized LGBTQ young people’s experiences on Facebook.

  3. The Best of Both Worlds? Online Ties and the Alternating Use of Social Network Sites in the Context of Migration

    Directory of Open Access Journals (Sweden)

    Jens F. Binder

    2014-12-01

    Full Text Available While an ever-growing body of research is concerned with user behavior on individual social network sites (SNSs—mostly Facebook—studies addressing an alternating use of two or more SNS are rare. Here, we investigate the relationship between alternating SNS use and social capital in the context of migration. Alternating SNS use avoids some of the problems associated with large networks located on one site; in particular the management of different social or cultural spheres. Not only does this strategy hold potential for increased social capital, it also provides a particular incentive for migrants faced with the challenge of staying in touch with back home and managing a new social environment. Two survey studies are presented that focus on the relationship between alternating SNS use and online ties in a migrant context involving Indian nationals. Study 1 looked at migration within India, whereas Study 2 compared international with domestic SNS users. In both studies, alternating SNS use added to the prediction of online network size and accounted for differences in network size found for migrant and non-migrant users. Differences were due to the number of peripheral ties, rather than core ties. Findings suggest that alternating SNS use may constitute a compensatory strategy that helps to overcome lower levels of socializing represented through a single SNS.

  4. Comparing the use of an online expert health network against common information sources to answer health questions.

    Science.gov (United States)

    Rhebergen, Martijn D F; Lenderink, Annet F; van Dijk, Frank J H; Hulshof, Carel T J

    2012-02-02

    Many workers have questions about occupational safety and health (OSH). It is unknown whether workers are able to find correct, evidence-based answers to OSH questions when they use common information sources, such as websites, or whether they would benefit from using an easily accessible, free-of-charge online network of OSH experts providing advice. To assess the rate of correct, evidence-based answers to OSH questions in a group of workers who used an online network of OSH experts (intervention group) compared with a group of workers who used common information sources (control group). In a quasi-experimental study, workers in the intervention and control groups were randomly offered 2 questions from a pool of 16 standardized OSH questions. Both questions were sent by mail to all participants, who had 3 weeks to answer them. The intervention group was instructed to use only the online network ArboAntwoord, a network of about 80 OSH experts, to solve the questions. The control group was instructed that they could use all information sources available to them. To assess answer correctness as the main study outcome, 16 standardized correct model answers were constructed with the help of reviewers who performed literature searches. Subsequently, the answers provided by all participants in the intervention (n = 94 answers) and control groups (n = 124 answers) were blinded and compared with the correct model answers on the degree of correctness. Of the 94 answers given by participants in the intervention group, 58 were correct (62%), compared with 24 of the 124 answers (19%) in the control group, who mainly used informational websites found via Google. The difference between the 2 groups was significant (rate difference = 43%, 95% confidence interval [CI] 30%-54%). Additional analysis showed that the rate of correct main conclusions of the answers was 85 of 94 answers (90%) in the intervention group and 75 of 124 answers (61%) in the control group (rate difference

  5. Connecting to young adults: an online social network survey of beliefs and attitudes associated with prescription opioid misuse among college students.

    Science.gov (United States)

    Lord, Sarah; Brevard, Julie; Budman, Simon

    2011-01-01

    A survey of motives and attitudes associated with patterns of nonmedical prescription opioid medication use among college students was conducted on Facebook, a popular online social networking Web site. Response metrics for a 2-week random advertisement post, targeting students who had misused prescription medications, surpassed typical benchmarks for online marketing campaigns and yielded 527 valid surveys. Respondent characteristics, substance use patterns, and use motives were consistent with other surveys of prescription opioid use among college populations. Results support the potential of online social networks to serve as powerful vehicles to connect with college-aged populations about their drug use. Limitations of the study are noted.

  6. Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems

    OpenAIRE

    Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

    2016-01-01

    It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed...

  7. An experimental study of the Online Information Paradox: Does en-route information improve road network performance?

    Science.gov (United States)

    Wijayaratna, Kasun P; Dixit, Vinayak V; Denant-Boemont, Laurent; Waller, S Travis

    2017-01-01

    This study investigates the empirical presence of a theoretical transportation paradox, defined as the "Online Information Paradox" (OIP). The paradox suggests that, for certain road networks, the provision of online information deteriorate travel conditions for all users of that network relative to the situation where no online information is provided to users. The analytical presence of the paradox was derived for a specific network structure by using two equilibrium models, the first being the Expected User Equilibrium (EUE) solution (no information scenario) and the other being the User Equilibrium with Recourse (UER) solution (with information scenario). An incentivised computerised route choice game was designed using the concepts of experimental economics and administered in a controlled laboratory environment to investigate the physical presence of the paradox. Aggregate statistics of path flows and Total System Travel Costs (TSTC) were used to compare the experimental results with the theoretical findings. A total of 12 groups of 12 participants completed the experiment and the OIP and the occurrence of the OIP being significant was observed in 11 of the 12 cases. Though information increased travel costs for users on average, it reduced the volatility of travel costs experienced in the no information scenario indicating that information can achieve a more reliable system. Further replications of similar experiments and more importantly field based identification of the phenomena will force transport professionals to be aware of the emergence of the paradox. In addition, studies such as this emphasise the need for the adoption of adaptive traffic assignment techniques to appropriately model the acquisition of information on a road network.

  8. An experimental study of the Online Information Paradox: Does en-route information improve road network performance?

    Directory of Open Access Journals (Sweden)

    Kasun P Wijayaratna

    Full Text Available This study investigates the empirical presence of a theoretical transportation paradox, defined as the "Online Information Paradox" (OIP. The paradox suggests that, for certain road networks, the provision of online information deteriorate travel conditions for all users of that network relative to the situation where no online information is provided to users. The analytical presence of the paradox was derived for a specific network structure by using two equilibrium models, the first being the Expected User Equilibrium (EUE solution (no information scenario and the other being the User Equilibrium with Recourse (UER solution (with information scenario. An incentivised computerised route choice game was designed using the concepts of experimental economics and administered in a controlled laboratory environment to investigate the physical presence of the paradox. Aggregate statistics of path flows and Total System Travel Costs (TSTC were used to compare the experimental results with the theoretical findings. A total of 12 groups of 12 participants completed the experiment and the OIP and the occurrence of the OIP being significant was observed in 11 of the 12 cases. Though information increased travel costs for users on average, it reduced the volatility of travel costs experienced in the no information scenario indicating that information can achieve a more reliable system. Further replications of similar experiments and more importantly field based identification of the phenomena will force transport professionals to be aware of the emergence of the paradox. In addition, studies such as this emphasise the need for the adoption of adaptive traffic assignment techniques to appropriately model the acquisition of information on a road network.

  9. A Network Analysis of Sexually Transmitted Diseases and Online Hookup Sites Among Men Who Have Sex With Men.

    Science.gov (United States)

    Chan, Philip A; Crowley, Christina; Rose, Jennifer S; Kershaw, Trace; Tributino, Alec; Montgomery, Madeline C; Almonte, Alexi; Raifman, Julia; Patel, Rupa; Nunn, Amy

    2018-07-01

    Sexually transmitted diseases (STDs) are increasing among gay, bisexual, and other men who have sex with men (MSM). Little is known about the use of websites and mobile phone applications to meet sexual partners ("hookup sites") and association with STD diagnoses. We performed a demographic and behavioral assessment of 415 MSM presenting to the Rhode Island STD clinic. Bivariate and multivariable analyses assessed associations between using hookup sites and testing positive for syphilis, gonorrhea, or chlamydia. Venue-based affiliation networks were created to evaluate hookup sites and their association with STD diagnoses. Among 415 MSM, 78% reported meeting a partner online in the last 12 months, and 25% tested positive for at least one STD. Men who met partners online were more likely to be white (67% vs. 54%, P = 0.03) and have more than 10 lifetime partners (87% vs. 58%, P Tinder (22%). In the multivariable analysis, only Scruff use was associated with testing positive for an STD (odds ratio, 2.28; 95% confidence interval, 1.09-4.94). However, among men who met partners online, 75% of men diagnosed as having an STD had met a sexual partner on Grindr, including 100% of those who were diagnosed as having gonorrhea. Use of hookup sites was nearly ubiquitous among MSM undergoing STD screening. Specific hookup sites were significantly associated with STD diagnoses among MSM. Greater efforts are needed to promote STD screening and prevention among MSM who meet partners online.

  10. Online Games

    OpenAIRE

    Kerr, Aphra; Ivory, James D.

    2015-01-01

    When we agreed to edit the theme on online games for this Encyclopedia our first question was, “What is meant by online games?” Scholars of games distinguish between nondigital games (such as board games) and digital games, rather than between online and offline games. With networked consoles and smartphones it is becoming harder and harder to find players in the wealthy industrialized countries who play “offline” digital games. Most games developers now include ...

  11. Development of an artificial neural network model for on-line thermal margin estimation of a nuclear reactor core

    International Nuclear Information System (INIS)

    Kim, Hyun Koon

    1992-02-01

    One of the key safety parameters related to thermal margin in a Pressurized Water Reactor (PWR) core, is Departure from Nucleate Boiling Ratio (DNBR), which is to be assessed and continuously monitored during operation via either an analog or a digital monitoring system. The digital monitoring system, in general, allows more thermal margin than the analog system through the on-line computation of DNBR using the measured parameters as inputs to a simplified, fast running computer code. The purpose of this thesis is to develop an advanced method for on-line DNBR estimation by introducing an artifactual neural network model for best-estimation of DNBR at the given reactor operating conditions. the neural network model, consisting of three layers with five operating parameters in the input layer, provides real-time prediction accuracy of DNBR by training the network against the detailed simulation results for various operating conditions. The overall training procedure is developed to learn the characteristics of DNBR behaviour in the reactor core. First, a set of random combination of input variables is generated by Latin Hypercube Sampling technique performed on a wide range of input parameters. Second, the target values of DNBR to be referenced for training are calculated using a detailed simulation code, COBRA-IV. Third, the optimized training input data are selected. Then, training is performed using an Error Back Propagation algorithm. After completion of training, the network is tested on the examining data set in order to investigate the generalization capability of the network responses for the steady state operating condition as well as for the transient situations where DNB is of a primary concern. The test results show that the values of DNBR predicted by the neural network are maintained at a high level of accuracy for the steady state condition, and are in good agreements with the transient situation, although slightly conservative as compared to those

  12. Things online social networking can take away: Reminders of social networking sites undermine the desirability of offline socializing and pleasures.

    Science.gov (United States)

    Li, Shiang-Shiang; Chang, Yevvon Yi-Chi; Chiou, Wen-Bin

    2017-04-01

    People are beginning to develop symbiotic relationships with social networking sites (SNSs), which provide users with abundant opportunities for social interaction. We contend that if people perceive SNSs as sources of social connection, the idea of SNSs may reduce the desire to pursue offline social activities and offline pleasures. Experiment 1 demonstrated that priming with SNSs was associated with a weakened desirability of offline social activities and an increased inclination to work alone. Felt relatedness mediated the link between SNS primes and reduced desire to engage in offline social activities. Experiment 2 showed that exposure to SNS primes reduced the desirability of offline socializing and lowered the desire for offline pleasurable experiences as well. Moreover, heavy users were more susceptible to this detrimental effect. We provide the first experimental evidence that the idea of online social networking may modulate users' engagement in offline social activities and offline pleasures. Hence, online social networking may satisfy the need for relatedness but undercut the likelihood of reaping enjoyment from offline social life. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

  13. Output Feedback-Based Boundary Control of Uncertain Coupled Semilinear Parabolic PDE Using Neurodynamic Programming.

    Science.gov (United States)

    Talaei, Behzad; Jagannathan, Sarangapani; Singler, John

    2018-04-01

    In this paper, neurodynamic programming-based output feedback boundary control of distributed parameter systems governed by uncertain coupled semilinear parabolic partial differential equations (PDEs) under Neumann or Dirichlet boundary control conditions is introduced. First, Hamilton-Jacobi-Bellman (HJB) equation is formulated in the original PDE domain and the optimal control policy is derived using the value functional as the solution of the HJB equation. Subsequently, a novel observer is developed to estimate the system states given the uncertain nonlinearity in PDE dynamics and measured outputs. Consequently, the suboptimal boundary control policy is obtained by forward-in-time estimation of the value functional using a neural network (NN)-based online approximator and estimated state vector obtained from the NN observer. Novel adaptive tuning laws in continuous time are proposed for learning the value functional online to satisfy the HJB equation along system trajectories while ensuring the closed-loop stability. Local uniformly ultimate boundedness of the closed-loop system is verified by using Lyapunov theory. The performance of the proposed controller is verified via simulation on an unstable coupled diffusion reaction process.

  14. Social networking site (SNS) use by adolescent mothers: Can social support and social capital be enhanced by online social networks? - A structured review of the literature.

    Science.gov (United States)

    Nolan, Samantha; Hendricks, Joyce; Ferguson, Sally; Towell, Amanda

    2017-05-01

    to critically appraise the available literature and summarise the evidence relating to adolescent mothers' use of social networking sites in terms of any social support and social capital they may provide and to identify areas for future exploration. social networking sites have been demonstrated to provide social support to marginalised individuals and provide psycho-social benefits to members of such groups. Adolescent mothers are at risk of; social marginalisation; anxiety disorders and depressive symptoms; and poorer health and educational outcomes for their children. Social support has been shown to benefit adolescent mothers thus online mechanisms require consideration. a review of original research articles METHOD: key terms and Boolean operators identified research reports across a 20-year timeframe pertaining to the area of enquiry in: CINAHL, Cochrane Library, Medline, Scopus, ERIC, ProQuest, PsychINFO, Web of Science, Health Collection (Informit) and Google Scholar databases. Eight original research articles met the inclusion criteria for this review. studies demonstrate that adolescent mothers actively search for health information using the Internet and social networking sites, and that social support and social capital can be attributed to their use of specifically created online groups from within targeted health interventions. Use of a message board forum for pregnant and parenting adolescents also demonstrates elements of social support. There are no studies to date pertaining to adolescent mothers' use of globally accessible social networking sites in terms of social support provision and related outcomes. further investigation is warranted to explore the potential benefits of adolescent mothers' use of globally accessible social networking sites in terms of any social support provision and social capital they may provide. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. An online method for lithium-ion battery remaining useful life estimation using importance sampling and neural networks

    International Nuclear Information System (INIS)

    Wu, Ji; Zhang, Chenbin; Chen, Zonghai

    2016-01-01

    Highlights: • An online RUL estimation method for lithium-ion battery is proposed. • RUL is described by the difference among battery terminal voltage curves. • A feed forward neural network is employed for RUL estimation. • Importance sampling is utilized to select feed forward neural network inputs. - Abstract: An accurate battery remaining useful life (RUL) estimation can facilitate the design of a reliable battery system as well as the safety and reliability of actual operation. A reasonable definition and an effective prediction algorithm are indispensable for the achievement of an accurate RUL estimation result. In this paper, the analysis of battery terminal voltage curves under different cycle numbers during charge process is utilized for RUL definition. Moreover, the relationship between RUL and charge curve is simulated by feed forward neural network (FFNN) for its simplicity and effectiveness. Considering the nonlinearity of lithium-ion charge curve, importance sampling (IS) is employed for FFNN input selection. Based on these results, an online approach using FFNN and IS is presented to estimate lithium-ion battery RUL in this paper. Experiments and numerical comparisons are conducted to validate the proposed method. The results show that the FFNN with IS is an accurate estimation method for actual operation.

  16. An on-line BCI for control of hand grasp sequence and holding using adaptive probabilistic neural network.

    Science.gov (United States)

    Hazrati, Mehrnaz Kh; Erfanian, Abbas

    2008-01-01

    This paper presents a new EEG-based Brain-Computer Interface (BCI) for on-line controlling the sequence of hand grasping and holding in a virtual reality environment. The goal of this research is to develop an interaction technique that will allow the BCI to be effective in real-world scenarios for hand grasp control. Moreover, for consistency of man-machine interface, it is desirable the intended movement to be what the subject imagines. For this purpose, we developed an on-line BCI which was based on the classification of EEG associated with imagination of the movement of hand grasping and resting state. A classifier based on probabilistic neural network (PNN) was introduced for classifying the EEG. The PNN is a feedforward neural network that realizes the Bayes decision discriminant function by estimating probability density function using mixtures of Gaussian kernels. Two types of classification schemes were considered here for on-line hand control: adaptive and static. In contrast to static classification, the adaptive classifier was continuously updated on-line during recording. The experimental evaluation on six subjects on different days demonstrated that by using the static scheme, a classification accuracy as high as the rate obtained by the adaptive scheme can be achieved. At the best case, an average classification accuracy of 93.0% and 85.8% was obtained using adaptive and static scheme, respectively. The results obtained from more than 1500 trials on six subjects showed that interactive virtual reality environment can be used as an effective tool for subject training in BCI.

  17. A systematic examination of the use of Online social networking sites for sexual health promotion

    Directory of Open Access Journals (Sweden)

    Hellard Margaret E

    2011-07-01

    Full Text Available Abstract Background In recent years social networking sites (SNSs have grown rapidly in popularity. The popularity of these sites, along with their interactive functions, offer a novel environment in which to deliver health promotion messages. The aim of this paper is to examine the extent to which SNSs are currently being used for sexual health promotion and describe the breadth of these activities. Methods We conducted a systematic search of published scientific literature, electronic sources (general and scientific search engines, blogs and SNSs (Facebook, MySpace to identify existing sexual health promotion activities using SNSs. Health promotion activities were eligible for inclusion if they related to sexual health or behaviour, utilised one or more SNSs, and involved some element of health promotion. Information regarding the source and type of health promotion activity, target population and site activity were extracted. Results 178 sexual health promotion activities met the inclusion criteria and were included in the review; only one activity was identified through a traditional systematic search of the published scientific literature. Activities most commonly used one SNS, were conducted by not-for-profit organisations, targeted young people and involved information delivery. Facebook was the most commonly used SNS (used by 71% of all health promotion activities identified, followed by MySpace and Twitter. Seventy nine percent of activities on MySpace were considered inactive as there had been no online posts within the past month, compared to 22% of activities using Facebook and 14% of activities using Twitter. The number of end-users and posts in the last seven days varied greatly between health promotion activities. Conclusions SNSs are being used for sexual health promotion, although the extent to which they are utilised varies greatly, and the vast majority of activities are unreported in the scientific literature. Future studies

  18. A systematic examination of the use of Online social networking sites for sexual health promotion

    Science.gov (United States)

    2011-01-01

    Background In recent years social networking sites (SNSs) have grown rapidly in popularity. The popularity of these sites, along with their interactive functions, offer a novel environment in which to deliver health promotion messages. The aim of this paper is to examine the extent to which SNSs are currently being used for sexual health promotion and describe the breadth of these activities. Methods We conducted a systematic search of published scientific literature, electronic sources (general and scientific search engines, blogs) and SNSs (Facebook, MySpace) to identify existing sexual health promotion activities using SNSs. Health promotion activities were eligible for inclusion if they related to sexual health or behaviour, utilised one or more SNSs, and involved some element of health promotion. Information regarding the source and type of health promotion activity, target population and site activity were extracted. Results 178 sexual health promotion activities met the inclusion criteria and were included in the review; only one activity was identified through a traditional systematic search of the published scientific literature. Activities most commonly used one SNS, were conducted by not-for-profit organisations, targeted young people and involved information delivery. Facebook was the most commonly used SNS (used by 71% of all health promotion activities identified), followed by MySpace and Twitter. Seventy nine percent of activities on MySpace were considered inactive as there had been no online posts within the past month, compared to 22% of activities using Facebook and 14% of activities using Twitter. The number of end-users and posts in the last seven days varied greatly between health promotion activities. Conclusions SNSs are being used for sexual health promotion, although the extent to which they are utilised varies greatly, and the vast majority of activities are unreported in the scientific literature. Future studies should examine the key

  19. Using online social networks to track a pandemic: A systematic review.

    Science.gov (United States)

    Al-Garadi, Mohammed Ali; Khan, Muhammad Sadiq; Varathan, Kasturi Dewi; Mujtaba, Ghulam; Al-Kabsi, Abdelkodose M

    2016-08-01

    The popularity and proliferation of online social networks (OSNs) have created massive social interaction among users that generate an extensive amount of data. An OSN offers a unique opportunity for studying and understanding social interaction and communication among far larger populations now more than ever before. Recently, OSNs have received considerable attention as a possible tool to track a pandemic because they can provide an almost real-time surveillance system at a less costly rate than traditional surveillance systems. A systematic literature search for studies with the primary aim of using OSN to detect and track a pandemic was conducted. We conducted an electronic literature search for eligible English articles published between 2004 and 2015 using PUBMED, IEEExplore, ACM Digital Library, Google Scholar, and Web of Science. First, the articles were screened on the basis of titles and abstracts. Second, the full texts were reviewed. All included studies were subjected to quality assessment. OSNs have rich information that can be utilized to develop an almost real-time pandemic surveillance system. The outcomes of OSN surveillance systems have demonstrated high correlations with the findings of official surveillance systems. However, the limitation in using OSN to track pandemic is in collecting representative data with sufficient population coverage. This challenge is related to the characteristics of OSN data. The data are dynamic, large-sized, and unstructured, thus requiring advanced algorithms and computational linguistics. OSN data contain significant information that can be used to track a pandemic. Different from traditional surveys and clinical reports, in which the data collection process is time consuming at costly rates, OSN data can be collected almost in real time at a cheaper cost. Additionally, the geographical and temporal information can provide exploratory analysis of spatiotemporal dynamics of infectious disease spread. However, on

  20. Share2Quit: Online Social Network Peer Marketing of Tobacco Cessation Systems.

    Science.gov (United States)

    Sadasivam, Rajani S; Cutrona, Sarah L; Luger, Tana M; Volz, Erik; Kinney, Rebecca; Rao, Sowmya R; Allison, Jeroan J; Houston, Thomas K

    2017-03-01

    Although technology-assisted tobacco interventions (TATIs) are effective, they are underused due to recruitment challenges. We tested whether we could successfully recruit smokers to a TATI using peer marketing through a social network (Facebook). We recruited smokers on Facebook using online advertisements. These recruited smokers (seeds) and subsequent waves of smokers (peer recruits) were provided the Share2Quit peer recruitment Facebook app and other tools. Smokers were incentivized for up to seven successful peer recruitments and had 30 days to recruit from date of registration. Successful peer recruitment was defined as a peer recruited smoker completing the registration on the TATI following a referral. Our primary questions were (1) whether smokers would recruit other smokers and (2) whether peer recruitment would extend the reach of the intervention to harder-to-reach groups, including those not ready to quit and minority smokers. Overall, 759 smokers were recruited (seeds: 190; peer recruits: 569). Fifteen percent (n = 117) of smokers successfully recruited their peers (seeds: 24.7%; peer recruits: 7.7%) leading to four recruitment waves. Compared to seeds, peer recruits were less likely to be ready to quit (peer recruits 74.2% vs. seeds 95.1%), more likely to be male (67.1% vs. 32.9%), and more likely to be African American (23.8% vs. 10.8%) (p marketing quadrupled our engaged smokers and enriched the sample with not-ready-to-quit and African American smokers. Peer recruitment is promising, and our study uncovered several important challenges for future research. This study demonstrates the successful recruitment of smokers to a TATI using a Facebook-based peer marketing strategy. Smokers on Facebook were willing and able to recruit other smokers to a TATI, yielding a large and diverse population of smokers. © The Author 2016. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For