Social Networking on the Semantic Web

Science.gov (United States)

Finin, Tim; Ding, Li; Zhou, Lina; Joshi, Anupam

2005-01-01

Purpose: Aims to investigate the way that the semantic web is being used to represent and process social network information. Design/methodology/approach: The Swoogle semantic web search engine was used to construct several large data sets of Resource Description Framework (RDF) documents with social network information that were encoded using the…

RECOMMENDER SYSTEMS IN SOCIAL NETWORKS

Directory of Open Access Journals (Sweden)

Cleomar Valois Batista Jr

2011-12-01

Full Text Available The continued and diversified growth of social networks has changed the way in which users interact with them. With these changes, what once was limited to social contact is now used for exchanging ideas and opinions, creating the need for new features. Users have so much information at their fingertips that they are unable to process it by themselves; hence, the need to develop new tools. Recommender systems were developed to address this need and many techniques were used for different approaches to the problem. To make relevant recommendations, these systems use large sets of data, not taking the social network of the user into consideration. Developing a recommender system that takes into account the social network of the user is another way of tackling the problem. The purpose of this project is to use the theory of six degrees of separation (Watts 2003 amongst users of a social network to enhance existing recommender systems.

Local Social Networks

DEFF Research Database (Denmark)

Sapuppo, Antonio; Sørensen, Lene Tolstrup

2011-01-01

Online social networks have become essential for many users in their daily communication. Through a combination of the online social networks with opportunistic networks, a new concept arises: Local Social Networks. The target of local social networks is to promote social networking benefits...... in physical environment in order to leverage personal affinities in the users' surroundings. The purpose of this paper is to present and discuss the concept of local social networks as a new social communication system. Particularly, the preliminary architecture and the prototype of local social networks...

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

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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…

Inferring personal economic status from social network location

Science.gov (United States)

Luo, Shaojun; Morone, Flaviano; Sarraute, Carlos; Travizano, Matías; Makse, Hernán A.

2017-05-01

It is commonly believed that patterns of social ties affect individuals' economic status. Here we translate this concept into an operational definition at the network level, which allows us to infer the economic well-being of individuals through a measure of their location and influence in the social network. We analyse two large-scale sources: telecommunications and financial data of a whole country's population. Our results show that an individual's location, measured as the optimal collective influence to the structural integrity of the social network, is highly correlated with personal economic status. The observed social network patterns of influence mimic the patterns of economic inequality. For pragmatic use and validation, we carry out a marketing campaign that shows a threefold increase in response rate by targeting individuals identified by our social network metrics as compared to random targeting. Our strategy can also be useful in maximizing the effects of large-scale economic stimulus policies.

Build your own social network laboratory with Social Lab: a tool for research in social media.

Science.gov (United States)

Garaizar, Pablo; Reips, Ulf-Dietrich

2014-06-01

Social networking has surpassed e-mail and instant messaging as the dominant form of online communication (Meeker, Devitt, & Wu, 2010). Currently, all large social networks are proprietary, making it difficult to impossible for researchers to make changes to such networks for the purpose of study design and access to user-generated data from the networks. To address this issue, the authors have developed and present Social Lab, an Internet-based free and open-source social network software system available from http://www.sociallab.es . Having full availability of navigation and communication data in Social Lab allows researchers to investigate behavior in social media on an individual and group level. Automated artificial users ("bots") are available to the researcher to simulate and stimulate social networking situations. These bots respond dynamically to situations as they unfold. The bots can easily be configured with scripts and can be used to experimentally manipulate social networking situations in Social Lab. Examples for setting up, configuring, and using Social Lab as a tool for research in social media are provided.

Opinion evolution in different social acquaintance networks.

Science.gov (United States)

Chen, Xi; Zhang, Xiao; Wu, Zhan; Wang, Hongwei; Wang, Guohua; Li, Wei

2017-11-01

Social acquaintance networks influenced by social culture and social policy have a great impact on public opinion evolution in daily life. Based on the differences between socio-culture and social policy, three different social acquaintance networks (kinship-priority acquaintance network, independence-priority acquaintance network, and hybrid acquaintance network) incorporating heredity proportion p h and variation proportion p v are proposed in this paper. Numerical experiments are conducted to investigate network topology and different phenomena during opinion evolution, using the Deffuant model. We found that in kinship-priority acquaintance networks, similar to the Chinese traditional acquaintance networks, opinions always achieve fragmentation, resulting in the formation of multiple large clusters and many small clusters due to the fact that individuals believe more in their relatives and live in a relatively closed environment. In independence-priority acquaintance networks, similar to Western acquaintance networks, the results are similar to those in the kinship-priority acquaintance network. In hybrid acquaintance networks, similar to the Chinese modern acquaintance networks, only a few clusters are formed indicating that in modern China, opinions are more likely to reach consensus on a large scale. These results are similar to the opinion evolution phenomena in modern society, proving the rationality and applicability of network models combined with social culture and policy. We also found a threshold curve p v +2p h =2.05 in the results for the final opinion clusters and evolution time. Above the threshold curve, opinions could easily reach consensus. Based on the above experimental results, a culture-policy-driven mechanism for the opinion dynamic is worth promoting in this paper, that is, opinion dynamics can be driven by different social cultures and policies through the influence of heredity and variation in interpersonal relationship networks. This

Large-scale brain networks in affective and social neuroscience: Towards an integrative functional architecture of the brain

Science.gov (United States)

Barrett, Lisa Feldman; Satpute, Ajay

2013-01-01

Understanding how a human brain creates a human mind ultimately depends on mapping psychological categories and concepts to physical measurements of neural response. Although it has long been assumed that emotional, social, and cognitive phenomena are realized in the operations of separate brain regions or brain networks, we demonstrate that it is possible to understand the body of neuroimaging evidence using a framework that relies on domain general, distributed structure-function mappings. We review current research in affective and social neuroscience and argue that the emerging science of large-scale intrinsic brain networks provides a coherent framework for a domain-general functional architecture of the human brain. PMID:23352202

Time Allocation in Social Networks: Correlation Between Social Structure and Human Communication Dynamics

Science.gov (United States)

Miritello, Giovanna; Lara, Rubén; Moro, Esteban

Recent research has shown the deep impact of the dynamics of human interactions (or temporal social networks) on the spreading of information, opinion formation, etc. In general, the bursty nature of human interactions lowers the interaction between people to the extent that both the speed and reach of information diffusion are diminished. Using a large database of 20 million users of mobile phone calls we show evidence this effect is not homogeneous in the social network but in fact, there is a large correlation between this effect and the social topological structure around a given individual. In particular, we show that social relations of hubs in a network are relatively weaker from the dynamical point than those that are poorer connected in the information diffusion process. Our results show the importance of the temporal patterns of communication when analyzing and modeling dynamical process on social networks.

Internet and social network recruitment: two case studies.

Science.gov (United States)

Johnson, Kathy A; Peace, Jane

2012-01-01

The recruitment of study participants is a significant research challenge. The Internet, with its ability to reach large numbers of people in networks connected by email, Facebook and other social networking mechanisms, appears to offer new avenues for recruitment. This paper reports recruitment experiences from two research projects that engaged the Internet and social networks in different ways for study recruitment. Drawing from the non-Internet recruitment literature, we speculate that the relationship with the source of the research and the purpose of the engaged social network should be a consideration in Internet or social network recruitment strategies.

Social networking mining, visualization, and security

CERN Document Server

Dehuri, Satchidananda; Wang, Gi-Nam

2014-01-01

With the proliferation of social media and on-line communities in networked world a large gamut of data has been collected and stored in databases. The rate at which such data is stored is growing at a phenomenal rate and pushing the classical methods of data analysis to their limits. This book presents an integrated framework of recent empirical and theoretical research on social network analysis based on a wide range of techniques from various disciplines like data mining, social sciences, mathematics, statistics, physics, network science, machine learning with visualization techniques, and security. The book illustrates the potential of multi-disciplinary techniques in various real life problems and intends to motivate researchers in social network analysis to design more effective tools by integrating swarm intelligence and data mining.  

The Social Network Classroom

Science.gov (United States)

Bunus, Peter

Online social networking is an important part in the everyday life of college students. Despite the increasing popularity of online social networking among students and faculty members, its educational benefits are largely untested. This paper presents our experience in using social networking applications and video content distribution websites as a complement of traditional classroom education. In particular, the solution has been based on effective adaptation, extension and integration of Facebook, Twitter, Blogger YouTube and iTunes services for delivering educational material to students on mobile platforms like iPods and 3 rd generation mobile phones. The goals of the proposed educational platform, described in this paper, are to make the learning experience more engaging, to encourage collaborative work and knowledge sharing among students, and to provide an interactive platform for the educators to reach students and deliver lecture material in a totally new way.

Factors Enabling Information Propagation in a Social Network Site

DEFF Research Database (Denmark)

Magnani, Matteo; Montesi, Danilo; Rossi, Luca

2013-01-01

A relevant feature of Social Network Sites is their ability to propagate units of information and create large distributed conversations. This phenomenon is particularly relevant because of the speed of information propagation, which is known to be much faster than within traditional media......, and because of the very large amount of people that can potentially be exposed to information items. While many general formal models of network propagation have been developed in different research fields, in this chapter we present the result of an empirical study on a Large Social Database (LSD) aimed...... at measuring specific socio-technical factors enabling information spreading in Social Network Sites....

Data Storage for Social Networks A Socially Aware Approach

CERN Document Server

Tran, Duc A

2012-01-01

Evidenced by the success of Facebook, Twitter, and LinkedIn, online social networks (OSNs) have become ubiquitous, offering novel ways for people to access information and communicate with each other. As the increasing popularity of social networking is undeniable, scalability is an important issue for any OSN that wants to serve a large number of users. Storing user data for the entire network on a single server can quickly lead to a bottleneck, and, consequently, more servers are needed to expand storage capacity and lower data request traffic per server. Adding more servers is just one step

Identifying influential user communities on the social network

Science.gov (United States)

Hu, Weishu; Gong, Zhiguo; Hou U, Leong; Guo, Jingzhi

2015-10-01

Nowadays social network services have been popularly used in electronic commerce systems. Users on the social network can develop different relationships based on their common interests and activities. In order to promote the business, it is interesting to explore hidden relationships among users developed on the social network. Such knowledge can be used to locate target users for different advertisements and to provide effective product recommendations. In this paper, we define and study a novel community detection problem that is to discover the hidden community structure in large social networks based on their common interests. We observe that the users typically pay more attention to those users who share similar interests, which enable a way to partition the users into different communities according to their common interests. We propose two algorithms to detect influential communities using common interests in large social networks efficiently and effectively. We conduct our experimental evaluation using a data set from Epinions, which demonstrates that our method achieves 4-11.8% accuracy improvement over the state-of-the-art method.

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.

Social Transmission of False Memory in Small Groups and Large Networks.

Science.gov (United States)

Maswood, Raeya; Rajaram, Suparna

2018-05-21

Sharing information and memories is a key feature of social interactions, making social contexts important for developing and transmitting accurate memories and also false memories. False memory transmission can have wide-ranging effects, including shaping personal memories of individuals as well as collective memories of a network of people. This paper reviews a collection of key findings and explanations in cognitive research on the transmission of false memories in small groups. It also reviews the emerging experimental work on larger networks and collective false memories. Given the reconstructive nature of memory, the abundance of misinformation in everyday life, and the variety of social structures in which people interact, an understanding of transmission of false memories has both scientific and societal implications. © 2018 Cognitive Science Society, Inc.

Social networks and cooperation in hunter-gatherers.

Science.gov (United States)

Apicella, Coren L; Marlowe, Frank W; Fowler, James H; Christakis, Nicholas A

2012-01-25

Social networks show striking structural regularities, and both theory and evidence suggest that networks may have facilitated the development of large-scale cooperation in humans. Here, we characterize the social networks of the Hadza, a population of hunter-gatherers in Tanzania. We show that Hadza networks have important properties also seen in modernized social networks, including a skewed degree distribution, degree assortativity, transitivity, reciprocity, geographic decay and homophily. We demonstrate that Hadza camps exhibit high between-group and low within-group variation in public goods game donations. Network ties are also more likely between people who give the same amount, and the similarity in cooperative behaviour extends up to two degrees of separation. Social distance appears to be as important as genetic relatedness and physical proximity in explaining assortativity in cooperation. Our results suggest that certain elements of social network structure may have been present at an early point in human history. Also, early humans may have formed ties with both kin and non-kin, based in part on their tendency to cooperate. Social networks may thus have contributed to the emergence of cooperation.

Conversation Analysis on Social Networking Sites

OpenAIRE

Belkaroui , Rami; Faiz , Rim; Elkhlifi , Aymen

2014-01-01

International audience; With the explosion of Web 2.0, people are becoming more communicative through expansion of services and multi-platform applications such as microblogs, forums and social networks which establishes social and collabora-tive backgrounds. These services can be seen as very large information repository containing millions of text messages usually organized into complex networks involving users interacting with each other at specific times. Several works focused only to ret...

Competing opinion diffusion on social networks.

Science.gov (United States)

Hu, Haibo

2017-11-01

Opinion competition is a common phenomenon in real life, such as with opinions on controversial issues or political candidates; however, modelling this competition remains largely unexplored. To bridge this gap, we propose a model of competing opinion diffusion on social networks taking into account degree-dependent fitness or persuasiveness. We study the combined influence of social networks, individual fitnesses and attributes, as well as mass media on people's opinions, and find that both social networks and mass media act as amplifiers in opinion diffusion, the amplifying effect of which can be quantitatively characterized. We analytically obtain the probability that each opinion will ultimately pervade the whole society when there are no committed people in networks, and the final proportion of each opinion at the steady state when there are committed people in networks. The results of numerical simulations show good agreement with those obtained through an analytical approach. This study provides insight into the collective influence of individual attributes, local social networks and global media on opinion diffusion, and contributes to a comprehensive understanding of competing diffusion behaviours in the real world.

Promoting Social Network Awareness: A Social Network Monitoring System

Science.gov (United States)

Cadima, Rita; Ferreira, Carlos; Monguet, Josep; Ojeda, Jordi; Fernandez, Joaquin

2010-01-01

To increase communication and collaboration opportunities, members of a community must be aware of the social networks that exist within that community. This paper describes a social network monitoring system--the KIWI system--that enables users to register their interactions and visualize their social networks. The system was implemented in a…

The Role of Social Networking Services in eParticipation

DEFF Research Database (Denmark)

Sæbø, Øystein; Rose, Jeremy; Nyvang, Tom

2009-01-01

, content-generation and the development of loosely-coupled communities. They provide the forum for much discussion and interaction. In this respect social networking could contribute to solve some of the problems of engaging their users that eParticipation services often struggle with. This paper...... and social networking because democratic systems favour the interests of larger groups of citizens --- the more voices behind a political proposition, the greater its chances of success. In this context of challenges the study of social networking on the internet and social network theory offers valuable...... insights into the practices and theories of citizen engagement. Social network theory focuses on the chains of relationships that social actors communicate and act within. Some social networking services on the internet attract large numbers of users, and apparently sustain a great deal of interaction...

Social Networks and Welfare in Future Animal Management.

Science.gov (United States)

Koene, Paul; Ipema, Bert

2014-03-17

It may become advantageous to keep human-managed animals in the social network groups to which they have adapted. Data concerning the social networks of farm animal species and their ancestors are scarce but essential to establishing the importance of a natural social network for farmed animal species. Social Network Analysis (SNA) facilitates the characterization of social networking at group, subgroup and individual levels. SNA is currently used for modeling the social behavior and management of wild animals and social welfare of zoo animals. It has been recognized for use with farm animals but has yet to be applied for management purposes. Currently, the main focus is on cattle, because in large groups (poultry), recording of individuals is expensive and the existence of social networks is uncertain due to on-farm restrictions. However, in many cases, a stable social network might be important to individual animal fitness, survival and welfare. For instance, when laying hens are not too densely housed, simple networks may be established. We describe here small social networks in horses, brown bears, laying hens and veal calves to illustrate the importance of measuring social networks among animals managed by humans. Emphasis is placed on the automatic measurement of identity, location, nearest neighbors and nearest neighbor distance for management purposes. It is concluded that social networks are important to the welfare of human-managed animal species and that welfare management based on automatic recordings will become available in the near future.

Predictors of Social Network Composition among Homeless and Runaway Adolescents

Science.gov (United States)

Johnson, K.D.; Whitbeck, L.B.; Hoyt, D.R.

2005-01-01

Recent research on the social support networks of homeless and runaway youth suggest the social networks of runaway youth are made up largely of transient deviant peer relationships. This paper examined social network characteristics of 428 homeless and runaway adolescents from small-to moderate-sized cities in four Midwestern states. We…

Professional social networking.

Science.gov (United States)

Rowley, Robert D

2014-12-01

We review the current state of social communication between healthcare professionals, the role of consumer social networking, and some emerging technologies to address the gaps. In particular, the review covers (1) the current state of loose social networking for continuing medical education (CME) and other broadcast information dissemination; (2) social networking for business promotion; (3) social networking for peer collaboration, including simple communication as well as more robust data-centered collaboration around patient care; and (4) engaging patients on social platforms, including integrating consumer-originated data into the mix of healthcare data. We will see how, as the nature of healthcare delivery moves from the institution-centric way of tradition to a more social and networked ambulatory pattern that we see emerging today, the nature of health IT has also moved from enterprise-centric systems to more socially networked, cloud-based options.

How can social networks ever become complex? Modelling the emergence of complex networks from local social exchanges

NARCIS (Netherlands)

Pujol, Josep M.; Flache, Andreas; Delgado, Jordi; Sangüesa, Ramon; Sanguessa, R.

2005-01-01

Small-world and power-law network structures have been prominently proposed as models of large networks. However, the assumptions of these models usually-lack sociological grounding. We present a computational model grounded in social exchange theory. Agents search attractive exchange partners in a

Social entrepreneurship and social networks

OpenAIRE

Dufays, Frédéric

2013-01-01

In this presentation, we argue that the sociology of social networks may provide interesting insights with regard to the emergence of social entrepreneurship both at micro and macro levels. There have already been several calls for research on social networks in the context of social entrepreneurship (Certo & Miller 2008; Gedajlovic, et al. 2013; Haugh 2007; Mair & Marti 2006; Short, et al. 2009). These calls often address the differences in structure and effects of social networks in a socia...

Social management of laboratory rhesus macaques housed in large groups using a network approach: A review.

Science.gov (United States)

McCowan, Brenda; Beisner, Brianne; Hannibal, Darcy

2017-12-07

Biomedical facilities across the nation and worldwide aim to develop cost-effective methods for the reproductive management of macaque breeding groups, typically by housing macaques in large, multi-male multi-female social groups that provide monkey subjects for research as well as appropriate socialization for their psychological well-being. One of the most difficult problems in managing socially housed macaques is their propensity for deleterious aggression. From a management perspective, deleterious aggression (as opposed to less intense aggression that serves to regulate social relationships) is undoubtedly the most problematic behavior observed in group-housed macaques, which can readily escalate to the degree that it causes social instability, increases serious physical trauma leading to group dissolution, and reduces psychological well-being. Thus for both welfare and other management reasons, aggression among rhesus macaques at primate centers and facilities needs to be addressed with a more proactive approach.Management strategies need to be instituted that maximize social housing while also reducing problematic social aggression due to instability using efficacious methods for detection and prevention in the most cost effective manner. Herein we review a new proactive approach using social network analysis to assess and predict deleterious aggression in macaque groups. We discovered three major pathways leading to instability, such as unusually high rates and severity of trauma and social relocations.These pathways are linked either directly or indirectly to network structure in rhesus macaque societies. We define these pathways according to the key intrinsic and extrinsic variables (e.g., demographic, genetic or social factors) that influence network and behavioral measures of stability (see Fig. 1). They are: (1) presence of natal males, (2) matrilineal genetic fragmentation, and (3) the power structure and conflict policing behavior supported by this

Brand communities embedded in social networks.

Science.gov (United States)

Zaglia, Melanie E

2013-02-01

Brand communities represent highly valuable marketing, innovation management, and customer relationship management tools. However, applying successful marketing strategies today, and in the future, also means exploring and seizing the unprecedented opportunities of social network environments. This study combines these two social phenomena which have largely been researched separately, and aims to investigate the existence, functionality and different types of brand communities within social networks. The netnographic approach yields strong evidence of this existence; leading to a better understanding of such embedded brand communities, their peculiarities, and motivational drivers for participation; therefore the findings contribute to theory by combining two separate research streams. Due to the advantages of social networks, brand management is now able to implement brand communities with less time and financial effort; however, choosing the appropriate brand community type, cultivating consumers' interaction, and staying tuned to this social engagement are critical factors to gain anticipated brand outcomes.

Social networks and cooperation: a bibliometric study

Directory of Open Access Journals (Sweden)

Ana Paula Lopes

2013-05-01

Full Text Available The social network analysis involves social and behavioral science. The decentralization of productive activities, such as the formation of "network organizations" as a result of downsizing of large corporate structures of the past, marked by outsoucing and formation of alliances, shows the importance of this theme. The main objective of this paper is to analyze the theory of cooperation and social networks over a period of 24 years. For this, was performed a bibliometric study with content analysis. The database chosen for the initial sample search was ISI Web of Science. The search topics were “social network” and “cooperation”. Were analyzed 97 articles and their references, through networks of citations. The main identified research groups dealing with issues related to trust, strategic alliances, natural cooperation, game theory, social capital, intensity of interaction, reciprocity and innovation. It was found that the publications occurred in a large number of journals, which indicates that the theme is multidisciplinary, and only five journals published at least three articles. Although the first publication has occurred in 1987, was from 2006 that the publications effectively increased. The areas most related to the theme of the research were performance, evolution, management, graphics, model and game theory.

Social Networks, Interpersonal Social Support, and Health Outcomes: A Health Communication Perspective

OpenAIRE

Wright, Kevin

2016-01-01

This manuscript discusses the development, impact, and several major research findings of studies in the area of social network support and health outcomes. The review focuses largely on the development of online social support networks and the ways in which they may interact with face-to-face support networks to influence physical and psychological health outcomes. The manuscript discusses this area, and it presents a research agenda for future work in this area from an Associate Editor’s pe...

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

State of the art applications of social network analysis

CERN Document Server

Can, Fazli; Polat, Faruk

2014-01-01

Social network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory, statistics, machine learning and data mining. This work covers frontier studies on social network analysis and mining from different perspectives such as social network sites, financial data, e-mails, forums, academic research funds, XML technology, blog content, community detection and clique finding, prediction of user

Too Many Friends: Social Integration, Network Cohesion and Adolescent Depressive Symptoms

Science.gov (United States)

Falci, Christina; McNeely, Clea

2009-01-01

Using a nationally representative sample of adolescents, we examine associations among social integration (network size), network cohesion (alter-density), perceptions of social relationships (e.g., social support) and adolescent depressive symptoms. We find that adolescents with either too large or too small a network have higher levels of…

Social Networks Use, Loneliness and Academic Performance among University Students

Science.gov (United States)

Stankovska, Gordana; Angelkovska, Slagana; Grncarovska, Svetlana Pandiloska

2016-01-01

The world is extensively changed by Social Networks Sites (SNSs) on the Internet. A large number of children and adolescents in the world have access to the internet and are exposed to the internet at a very early age. Most of them use the Social Networks Sites with the purpose of exchanging academic activities and developing a social network all…

A comparative analysis of the statistical properties of large mobile phone calling networks.

Science.gov (United States)

Li, Ming-Xia; Jiang, Zhi-Qiang; Xie, Wen-Jie; Miccichè, Salvatore; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N

2014-05-30

Mobile phone calling is one of the most widely used communication methods in modern society. The records of calls among mobile phone users provide us a valuable proxy for the understanding of human communication patterns embedded in social networks. Mobile phone users call each other forming a directed calling network. If only reciprocal calls are considered, we obtain an undirected mutual calling network. The preferential communication behavior between two connected users can be statistically tested and it results in two Bonferroni networks with statistically validated edges. We perform a comparative analysis of the statistical properties of these four networks, which are constructed from the calling records of more than nine million individuals in Shanghai over a period of 110 days. We find that these networks share many common structural properties and also exhibit idiosyncratic features when compared with previously studied large mobile calling networks. The empirical findings provide us an intriguing picture of a representative large social network that might shed new lights on the modelling of large social networks.

Brand communities embedded in social networks ?

OpenAIRE

Zaglia, Melanie E.

2013-01-01

Brand communities represent highly valuable marketing, innovation management, and customer relationship management tools. However, applying successful marketing strategies today, and in the future, also means exploring and seizing the unprecedented opportunities of social network environments. This study combines these two social phenomena which have largely been researched separately, and aims to investigate the existence, functionality and different types of brand communities within social ...

Social networks a real solution for students' future jobs

Directory of Open Access Journals (Sweden)

Lorena Bătăgan

2015-11-01

Full Text Available This study examines if social networks represent a real solution for students' future jobs. The authors use for their analysis data provided by the students from Faculty of Economic Cybernetics, Statistics and Informatics (ECSI ‒ The Bucharest University of Economic Studies and by professional networking websites like Facebook and LinkedIn. In this paper there are highlighted the level of using social networks and students’ perception on the use of social networks in their activities. The paper focuses on students’ interest in using social networks for securing future jobs. The results of research underlined the idea that for higher education there is an opportunity to facilitate the access of students to social networks in two ways: by developing or enhancing students’ knowledge on how to use social networks and as part of that effort, by educating students about how they can promote their skills. The main idea is that the use of large amounts of data generated by social networks accelerates students' integration within working environment and their employment.

Social network, social support, and risk of incident stroke: Atherosclerosis Risk in Communities study.

Science.gov (United States)

Nagayoshi, Mako; Everson-Rose, Susan A; Iso, Hiroyasu; Mosley, Thomas H; Rose, Kathryn M; Lutsey, Pamela L

2014-10-01

Having a small social network and lack of social support have been associated with incident coronary heart disease; however, epidemiological evidence for incident stroke is limited. We assessed the longitudinal association of a small social network and lack of social support with risk of incident stroke and evaluated whether the association was partly mediated by vital exhaustion and inflammation. The Atherosclerosis Risk in Communities study measured social network and social support in 13 686 men and women (mean, 57 years; 56% women; 24% black; 76% white) without a history of stroke. Social network was assessed by the 10-item Lubben Social Network Scale and social support by a 16-item Interpersonal Support Evaluation List-Short Form. During a median follow-up of 18.6 years, 905 incident strokes occurred. Relative to participants with a large social network, those with a small social network had a higher risk of stroke (hazard ratio [95% confidence interval], 1.44 [1.02-2.04]) after adjustment for demographics, socioeconomic variables, marital status, behavioral risk factors, and major stroke risk factors. Vital exhaustion, but not inflammation, partly mediated the association between a small social network and incident stroke. Social support was unrelated to incident stroke. In this sample of US community-dwelling men and women, having a small social network was associated with excess risk of incident stroke. As with other cardiovascular conditions, having a small social network may be associated with a modestly increased risk of incident stroke. © 2014 American Heart Association, Inc.

Social network data analytics

CERN Document Server

Aggarwal, Charu C

2011-01-01

Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Pr

Physical Proximity and Spreading in Dynamic Social Networks

OpenAIRE

Stopczynski, Arkadiusz; Pentland, Alex Sandy; Lehmann, Sune

2015-01-01

Most infectious diseases spread on a dynamic network of human interactions. Recent studies of social dynamics have provided evidence that spreading patterns may depend strongly on detailed micro-dynamics of the social system. We have recorded every single interaction within a large population, mapping out---for the first time at scale---the complete proximity network for a densely-connected system. Here we show the striking impact of interaction-distance on the network structure and dynamics ...

Internet and Social Network Recruitment: Two Case Studies

OpenAIRE

Johnson, Kathy A.; Peace, Jane

2012-01-01

The recruitment of study participants is a significant research challenge. The Internet, with its ability to reach large numbers of people in networks connected by email, Facebook and other social networking mechanisms, appears to offer new avenues for recruitment. This paper reports recruitment experiences from two research projects that engaged the Internet and social networks in different ways for study recruitment. Drawing from the non-Internet recruitment literature, we speculate that th...

Identifying and tracking dynamic processes in social networks

Science.gov (United States)

Chung, Wayne; Savell, Robert; Schütt, Jan-Peter; Cybenko, George

2006-05-01

The detection and tracking of embedded malicious subnets in an active social network can be computationally daunting due to the quantity of transactional data generated in the natural interaction of large numbers of actors comprising a network. In addition, detection of illicit behavior may be further complicated by evasive strategies designed to camouflage the activities of the covert subnet. In this work, we move beyond traditional static methods of social network analysis to develop a set of dynamic process models which encode various modes of behavior in active social networks. These models will serve as the basis for a new application of the Process Query System (PQS) to the identification and tracking of covert dynamic processes in social networks. We present a preliminary result from application of our technique in a real-world data stream-- the Enron email corpus.

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...

Returns to Social Network Capital among Traders

OpenAIRE

Marcel Fafchamps; Bart Minten

2000-01-01

Using data on agricultural traders in Madagascar, this paper shows that social network capital has a large effect on firm productivity. Better connected traders have significantly larger sales and value added than less connected traders after controlling for physical and human inputs as well as for entrepreneur characteristics. The analysis indicates that three dimensions of social network capital should be distinguished: relationships with other traders, which among other things help firms e...

Appplication of statistical mechanical methods to the modeling of social networks

Science.gov (United States)

Strathman, Anthony Robert

With the recent availability of large-scale social data sets, social networks have become open to quantitative analysis via the methods of statistical physics. We examine the statistical properties of a real large-scale social network, generated from cellular phone call-trace logs. We find this network, like many other social networks to be assortative (r = 0.31) and clustered (i.e., strongly transitive, C = 0.21). We measure fluctuation scaling to identify the presence of internal structure in the network and find that structural inhomogeneity effectively disappears at the scale of a few hundred nodes, though there is no sharp cutoff. We introduce an agent-based model of social behavior, designed to model the formation and dissolution of social ties. The model is a modified Metropolis algorithm containing agents operating under the basic sociological constraints of reciprocity, communication need and transitivity. The model introduces the concept of a social temperature. We go on to show that this simple model reproduces the global statistical network features (incl. assortativity, connected fraction, mean degree, clustering, and mean shortest path length) of the real network data and undergoes two phase transitions, one being from a "gas" to a "liquid" state and the second from a liquid to a glassy state as function of this social temperature.

Social Network Types and Acute Stroke Preparedness Behavior

Directory of Open Access Journals (Sweden)

Bernadette Boden-Albala

2011-08-01

Full Text Available Objectives: Presence of informal social networks has been associated with favorable health and behaviors, but whether different types of social networks impact on different health outcomes remains largely unknown. We examined the associations of different social network types (marital dyad, household, friendship, and informal community networks with acute stroke preparedness behavior. We hypothesized that marital dyad best matched the required tasks and is the most effective network type for this behavior. Methods: We collected in-person interview and medical record data for 1,077 adults diagnosed with stroke and transient ischemic attack. We used logistic regression analyses to examine the association of each social network with arrival at the emergency department (ED within 3 h of stroke symptoms. Results: Adjusting for age, race-ethnicity, education, gender, transportation type to ED and vascular diagnosis, being married or living with a partner was significantly associated with early arrival at the ED (odds ratio = 2.0, 95% confidence interval: 1.2–3.1, but no significant univariate or multivariate associations were observed for household, friendship, and community networks. Conclusions: The marital/partnership dyad is the most influential type of social network for stroke preparedness behavior.

Social Networks of Lesbian, Gay, Bisexual, and Transgender Older Adults.

Science.gov (United States)

Erosheva, Elena A; Kim, Hyun-Jun; Emlet, Charles; Fredriksen-Goldsen, Karen I

2016-01-01

This study examines global social networks-including friendship, support, and acquaintance networks-of lesbian, gay, bisexual, and transgender (LGBT) older adults. Utilizing data from a large community-based study, we employ multiple regression analyses to examine correlates of social network size and diversity. Controlling for background characteristics, network size was positively associated with being female, transgender identity, employment, higher income, having a partner or a child, identity disclosure to a neighbor, engagement in religious activities, and service use. Controlling in addition for network size, network diversity was positively associated with younger age, being female, transgender identity, identity disclosure to a friend, religious activity, and service use. According to social capital theory, social networks provide a vehicle for social resources that can be beneficial for successful aging and well-being. This study is a first step at understanding the correlates of social network size and diversity among LGBT older adults. © The Author(s) 2015.

Origin of Peer Influence in Social Networks

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Pinheiro, Flávio L.; Santos, Marta D.; Santos, Francisco C.; Pacheco, Jorge M.

2014-03-01

Social networks pervade our everyday lives: we interact, influence, and are influenced by our friends and acquaintances. With the advent of the World Wide Web, large amounts of data on social networks have become available, allowing the quantitative analysis of the distribution of information on them, including behavioral traits and fads. Recent studies of correlations among members of a social network, who exhibit the same trait, have shown that individuals influence not only their direct contacts but also friends' friends, up to a network distance extending beyond their closest peers. Here, we show how such patterns of correlations between peers emerge in networked populations. We use standard models (yet reflecting intrinsically different mechanisms) of information spreading to argue that empirically observed patterns of correlation among peers emerge naturally from a wide range of dynamics, being essentially independent of the type of information, on how it spreads, and even on the class of underlying network that interconnects individuals. Finally, we show that the sparser and clustered the network, the more far reaching the influence of each individual will be.

Crawling Facebook for Social Network Analysis Purposes

OpenAIRE

Catanese, Salvatore A.; De Meo, Pasquale; Ferrara, Emilio; Fiumara, Giacomo; Provetti, Alessandro

2011-01-01

We describe our work in the collection and analysis of massive data describing the connections between participants to online social networks. Alternative approaches to social network data collection are defined and evaluated in practice, against the popular Facebook Web site. Thanks to our ad-hoc, privacy-compliant crawlers, two large samples, comprising millions of connections, have been collected; the data is anonymous and organized as an undirected graph. We describe a set of tools that w...

Memory Transmission in Small Groups and Large Networks: An Agent-Based Model.

Science.gov (United States)

Luhmann, Christian C; Rajaram, Suparna

2015-12-01

The spread of social influence in large social networks has long been an interest of social scientists. In the domain of memory, collaborative memory experiments have illuminated cognitive mechanisms that allow information to be transmitted between interacting individuals, but these experiments have focused on small-scale social contexts. In the current study, we took a computational approach, circumventing the practical constraints of laboratory paradigms and providing novel results at scales unreachable by laboratory methodologies. Our model embodied theoretical knowledge derived from small-group experiments and replicated foundational results regarding collaborative inhibition and memory convergence in small groups. Ultimately, we investigated large-scale, realistic social networks and found that agents are influenced by the agents with which they interact, but we also found that agents are influenced by nonneighbors (i.e., the neighbors of their neighbors). The similarity between these results and the reports of behavioral transmission in large networks offers a major theoretical insight by linking behavioral transmission to the spread of information. © The Author(s) 2015.

Social networks

CERN Document Server

Etaner-Uyar, A Sima

2014-01-01

The present volume provides a comprehensive resource for practitioners and researchers alike-both those new to the field as well as those who already have some experience. The work covers Social Network Analysis theory and methods with a focus on current applications and case studies applied in various domains such as mobile networks, security, machine learning and health. With the increasing popularity of Web 2.0, social media has become a widely used communication platform. Parallel to this development, Social Network Analysis gained in importance as a research field, while opening up many

Offspring social network structure predicts fitness in families.

Science.gov (United States)

Royle, Nick J; Pike, Thomas W; Heeb, Philipp; Richner, Heinz; Kölliker, Mathias

2012-12-22

Social structures such as families emerge as outcomes of behavioural interactions among individuals, and can evolve over time if families with particular types of social structures tend to leave more individuals in subsequent generations. The social behaviour of interacting individuals is typically analysed as a series of multiple dyadic (pair-wise) interactions, rather than a network of interactions among multiple individuals. However, in species where parents feed dependant young, interactions within families nearly always involve more than two individuals simultaneously. Such social networks of interactions at least partly reflect conflicts of interest over the provision of costly parental investment. Consequently, variation in family network structure reflects variation in how conflicts of interest are resolved among family members. Despite its importance in understanding the evolution of emergent properties of social organization such as family life and cooperation, nothing is currently known about how selection acts on the structure of social networks. Here, we show that the social network structure of broods of begging nestling great tits Parus major predicts fitness in families. Although selection at the level of the individual favours large nestlings, selection at the level of the kin-group primarily favours families that resolve conflicts most effectively.

Social cognitive radio networks

CERN Document Server

Chen, Xu

2015-01-01

This brief presents research results on social cognitive radio networks, a transformational and innovative networking paradigm that promotes the nexus between social interactions and cognitive radio networks. Along with a review of the research literature, the text examines the key motivation and challenges of social cognitive radio network design. Three socially inspired distributed spectrum sharing mechanisms are introduced: adaptive channel recommendation mechanism, imitation-based social spectrum sharing mechanism, and evolutionarily stable spectrum access mechanism. The brief concludes with a discussion of future research directions which ascertains that exploiting social interactions for distributed spectrum sharing will advance the state-of-the-art of cognitive radio network design, spur a new line of thinking for future wireless networks, and enable novel wireless service and applications.

Detecting the influence of spreading in social networks with excitable sensor networks.

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Sen Pei

Full Text Available Detecting spreading outbreaks in social networks with sensors is of great significance in applications. Inspired by the formation mechanism of humans' physical sensations to external stimuli, we propose a new method to detect the influence of spreading by constructing excitable sensor networks. Exploiting the amplifying effect of excitable sensor networks, our method can better detect small-scale spreading processes. At the same time, it can also distinguish large-scale diffusion instances due to the self-inhibition effect of excitable elements. Through simulations of diverse spreading dynamics on typical real-world social networks (Facebook, coauthor, and email social networks, we find that the excitable sensor networks are capable of detecting and ranking spreading processes in a much wider range of influence than other commonly used sensor placement methods, such as random, targeted, acquaintance and distance strategies. In addition, we validate the efficacy of our method with diffusion data from a real-world online social system, Twitter. We find that our method can detect more spreading topics in practice. Our approach provides a new direction in spreading detection and should be useful for designing effective detection methods.

Social Networks and the Environment

OpenAIRE

Julio Videras

2013-01-01

This review discusses empirical research on social networks and the environment; it summarizes findings from representative studies and the conceptual frameworks social scientists use to examine the role of social networks. The article presents basic concepts in social network analysis, summarizes common challenges of empirical research on social networks, and outlines areas for future research. Finally, the article discusses the normative and positive meanings of social networks.

Practical characterization of large networks using neighborhood information

KAUST Repository

Wang, Pinghui

2018-02-14

Characterizing large complex networks such as online social networks through node querying is a challenging task. Network service providers often impose severe constraints on the query rate, hence limiting the sample size to a small fraction of the total network of interest. Various ad hoc subgraph sampling methods have been proposed, but many of them give biased estimates and no theoretical basis on the accuracy. In this work, we focus on developing sampling methods for large networks where querying a node also reveals partial structural information about its neighbors. Our methods are optimized for NoSQL graph databases (if the database can be accessed directly), or utilize Web APIs available on most major large networks for graph sampling. We show that our sampling method has provable convergence guarantees on being an unbiased estimator, and it is more accurate than state-of-the-art methods. We also explore methods to uncover shortest paths between a subset of nodes and detect high degree nodes by sampling only a small fraction of the network of interest. Our results demonstrate that utilizing neighborhood information yields methods that are two orders of magnitude faster than state-of-the-art methods.

Understanding how social networking influences perceived satisfaction with conference experiences

Science.gov (United States)

van Riper, Carena J.; van Riper, Charles; Kyle, Gerard T.; Lee, Martha E.

2013-01-01

Social networking is a key benefit derived from participation in conferences that bind the ties of a professional community. Building social networks can lead to satisfactory experiences while furthering participants' long- and short-term career goals. Although investigations of social networking can lend insight into how to effectively engage individuals and groups within a professional cohort, this area has been largely overlooked in past research. The present study investigates the relationship between social networking and satisfaction with the 10th Biennial Conference of Research on the Colorado Plateau using structural equation modelling. Results partially support the hypothesis that three dimensions of social networking – interpersonal connections, social cohesion, and secondary associations – positively contribute to the performance of various conference attributes identified in two focus group sessions. The theoretical and applied contributions of this paper shed light on the social systems formed within professional communities and resource allocation among service providers.

Emotion shapes the diffusion of moralized content in social networks.

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Brady, William J; Wills, Julian A; Jost, John T; Tucker, Joshua A; Van Bavel, Jay J

2017-07-11

Political debate concerning moralized issues is increasingly common in online social networks. However, moral psychology has yet to incorporate the study of social networks to investigate processes by which some moral ideas spread more rapidly or broadly than others. Here, we show that the expression of moral emotion is key for the spread of moral and political ideas in online social networks, a process we call "moral contagion." Using a large sample of social media communications about three polarizing moral/political issues ( n = 563,312), we observed that the presence of moral-emotional words in messages increased their diffusion by a factor of 20% for each additional word. Furthermore, we found that moral contagion was bounded by group membership; moral-emotional language increased diffusion more strongly within liberal and conservative networks, and less between them. Our results highlight the importance of emotion in the social transmission of moral ideas and also demonstrate the utility of social network methods for studying morality. These findings offer insights into how people are exposed to moral and political ideas through social networks, thus expanding models of social influence and group polarization as people become increasingly immersed in social media networks.

Spatio-temporal keyword queries in social networks

DEFF Research Database (Denmark)

Cozza, V.; Messina, Alessandro; Montesi, D.

2013-01-01

Due to the large amount of social network data produced at an ever growing speed and their complex nature, recent works have addressed the problem of efficiently querying such data according to social, temporal or spatial dimensions. In this work we propose a data model that keeps into account al...

Social Networks of Lesbian, Gay, Bisexual, and Transgender Older Adults

Science.gov (United States)

Erosheva, Elena A.; Kim, Hyun-Jun; Emlet, Charles; Fredriksen-Goldsen, Karen I.

2015-01-01

Purpose This study examines global social networks—including friendship, support, and acquaintance networks—of lesbian, gay, bisexual, and transgender (LGBT) older adults. Design and Methods Utilizing data from a large community-based study, we employ multiple regression analyses to examine correlates of social network size and diversity. Results Controlling for background characteristics, network size was positively associated with being female, transgender identity, employment, higher income, having a partner or a child, identity disclosure to a neighbor, engagement in religious activities, and service use. Controlling in addition for network size, network diversity was positively associated with younger age, being female, transgender identity, identity disclosure to a friend, religious activity, and service use. Implications According to social capital theory, social networks provide a vehicle for social resources that can be beneficial for successful aging and well-being. This study is a first step at understanding the correlates of social network size and diversity among LGBT older adults. PMID:25882129

Suicide ideation of individuals in online social networks.

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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.

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.

Social structure of Facebook networks

Science.gov (United States)

Traud, Amanda L.; Mucha, Peter J.; Porter, Mason A.

2012-08-01

We study the social structure of Facebook “friendship” networks at one hundred American colleges and universities at a single point in time, and we examine the roles of user attributes-gender, class year, major, high school, and residence-at these institutions. We investigate the influence of common attributes at the dyad level in terms of assortativity coefficients and regression models. We then examine larger-scale groupings by detecting communities algorithmically and comparing them to network partitions based on user characteristics. We thereby examine the relative importance of different characteristics at different institutions, finding for example that common high school is more important to the social organization of large institutions and that the importance of common major varies significantly between institutions. Our calculations illustrate how microscopic and macroscopic perspectives give complementary insights on the social organization at universities and suggest future studies to investigate such phenomena further.

Relationship between Social Networks Adoption and Social Intelligence

Science.gov (United States)

Gunduz, Semseddin

2017-01-01

The purpose of this study was to set forth the relationship between the individuals' states to adopt social networks and social intelligence and analyze both concepts according to various variables. Research data were collected from 1145 social network users in the online media by using the Adoption of Social Network Scale and Social Intelligence…

SOCIAL NETWORK EFFECTS ON ROMANTIC RELATIONSHIP

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Fatma CAN

2015-06-01

Full Text Available The main objective of the study was to obtain information about social network variables in order to predict the relational commitment of married individuals and people having dating relationships. For this purpose, social network analysis has been carried out on 134 people having dating relationship and 154 married individuals and then Relationship Stability Scale, Subjective Norm Scale and Social Network Feature Survey prepared by the researcher were used. The results indicated that the approval of the closest social network member and the level of enjoyment of each other’s social network members had the best predictive value for relationship satisfaction and the investment to the relationship. The results also demonstrated that, approval of the social network had a negative impact on the level of the quality of alternatives and it showed that social networks were seen as a barrier function to have alternative relationships. Furthermore, by dividing social network members into two groups, for the dating group, the approval of the social network was the most significant variable for commitment but in the married group, the need for social network approval was not an important criteria because of having their relatioship already confirmed legally. When social network members were categorised and examined, the closest social network members did not differ by sex, but were varied in terms of relationship types. In the flirt group, one of their friends among his/her social network and their partners’ social network was specified as the closest social network member whereas in the married group, the closest social network member among his/her social network was their mother while it was their sibling among partner’s social network.

Emotion shapes the diffusion of moralized content in social networks

Science.gov (United States)

Wills, Julian A.; Jost, John T.; Tucker, Joshua A.; Van Bavel, Jay J.

2017-01-01

Political debate concerning moralized issues is increasingly common in online social networks. However, moral psychology has yet to incorporate the study of social networks to investigate processes by which some moral ideas spread more rapidly or broadly than others. Here, we show that the expression of moral emotion is key for the spread of moral and political ideas in online social networks, a process we call “moral contagion.” Using a large sample of social media communications about three polarizing moral/political issues (n = 563,312), we observed that the presence of moral-emotional words in messages increased their diffusion by a factor of 20% for each additional word. Furthermore, we found that moral contagion was bounded by group membership; moral-emotional language increased diffusion more strongly within liberal and conservative networks, and less between them. Our results highlight the importance of emotion in the social transmission of moral ideas and also demonstrate the utility of social network methods for studying morality. These findings offer insights into how people are exposed to moral and political ideas through social networks, thus expanding models of social influence and group polarization as people become increasingly immersed in social media networks. PMID:28652356

The effects of types of social networks, perceived social support, and loneliness on the health of older people: accounting for the social context.

Science.gov (United States)

Stephens, Christine; Alpass, Fiona; Towers, Andy; Stevenson, Brendan

2011-09-01

To use an ecological model of ageing (Berkman, Glass, Brissette, & Seeman, 2000) which includes upstream social context factors and downstream social support factors to examine the effects of social networks on health. Postal survey responses from a representative population sample of New Zealanders aged 55 to 70 years (N = 6,662). Correlations and multiple regression analyses provided support for a model in which social context contributes to social network type, which affects perceived social support and loneliness, and consequent mental and physical health. Ethnicity was related to social networks and health but this was largely accounted for by other contextual variables measuring socioeconomic status. Gender and age were also significant variables in the model. Social network type is a useful way to assess social integration within this model of cascading effects. More detailed information could be gained through the development of our network assessment instruments for older people.

Psychology and social networks: a dynamic network theory perspective.

Science.gov (United States)

Westaby, James D; Pfaff, Danielle L; Redding, Nicholas

2014-04-01

Research on social networks has grown exponentially in recent years. However, despite its relevance, the field of psychology has been relatively slow to explain the underlying goal pursuit and resistance processes influencing social networks in the first place. In this vein, this article aims to demonstrate how a dynamic network theory perspective explains the way in which social networks influence these processes and related outcomes, such as goal achievement, performance, learning, and emotional contagion at the interpersonal level of analysis. The theory integrates goal pursuit, motivation, and conflict conceptualizations from psychology with social network concepts from sociology and organizational science to provide a taxonomy of social network role behaviors, such as goal striving, system supporting, goal preventing, system negating, and observing. This theoretical perspective provides psychologists with new tools to map social networks (e.g., dynamic network charts), which can help inform the development of change interventions. Implications for social, industrial-organizational, and counseling psychology as well as conflict resolution are discussed, and new opportunities for research are highlighted, such as those related to dynamic network intelligence (also known as cognitive accuracy), levels of analysis, methodological/ethical issues, and the need to theoretically broaden the study of social networking and social media behavior. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Privacy in social networking sites

OpenAIRE

Λεονάρδος, Γεώργιος; Leonardos, Giorgos

2016-01-01

The purpose of this study is to explore the aspects of privacy over the use of social networks web sites. More specific, we will show the types of social networks, their privacy mechanisms that are different in each social network site, their privacy options that are offered to users. We will report some serious privacy violations incidents of the most popular social networks sites such as Facebook, Twitter, LinkedIn. Also, we will report some important surveys about social networks and pr...

Social traits, social networks and evolutionary biology.

Science.gov (United States)

Fisher, D N; McAdam, A G

2017-12-01

The social environment is both an important agent of selection for most organisms, and an emergent property of their interactions. As an aggregation of interactions among members of a population, the social environment is a product of many sets of relationships and so can be represented as a network or matrix. Social network analysis in animals has focused on why these networks possess the structure they do, and whether individuals' network traits, representing some aspect of their social phenotype, relate to their fitness. Meanwhile, quantitative geneticists have demonstrated that traits expressed in a social context can depend on the phenotypes and genotypes of interacting partners, leading to influences of the social environment on the traits and fitness of individuals and the evolutionary trajectories of populations. Therefore, both fields are investigating similar topics, yet have arrived at these points relatively independently. We review how these approaches are diverged, and yet how they retain clear parallelism and so strong potential for complementarity. This demonstrates that, despite separate bodies of theory, advances in one might inform the other. Techniques in network analysis for quantifying social phenotypes, and for identifying community structure, should be useful for those studying the relationship between individual behaviour and group-level phenotypes. Entering social association matrices into quantitative genetic models may also reduce bias in heritability estimates, and allow the estimation of the influence of social connectedness on trait expression. Current methods for measuring natural selection in a social context explicitly account for the fact that a trait is not necessarily the property of a single individual, something the network approaches have not yet considered when relating network metrics to individual fitness. Harnessing evolutionary models that consider traits affected by genes in other individuals (i.e. indirect genetic

PERSON IN SOCIAL NETWORKS

Directory of Open Access Journals (Sweden)

Андрей Борисович Шалимов

2013-11-01

Full Text Available Purpose: Our scientific purpose is creation of practical model of person’s representation in social networks (Facebook, Twitter, Classmates. As user of social networks, person is made conditional not only upon its own identity, but also upon the information about himself, which he is ready to share with his friends in contact list. Goal-setting and practical activities for their achievement mean that you should apply force, it can completely eliminates systemic factors, the system of power relations, which overwhelms human being in social networks.Methodology: The reconstruction of the model of human in the popularity of social networksResults: There is descripton of practical model of person's representation in social networks, it includes the management of own identity and the audience (the list of contacts. When person manages own identity, he answers the question, «Whom I can dare to be?». Person perceives himself in social networks' being, he understands himself and his place in the world, he identifies.Managing the way in social media means that you answer the question «What I want to tell?». Person in social media looks at events in the field of culture, economy, politics, social relations through the prism of his own attitudes, he forms and formulates his own agenda and he is going to tell about himself through them.Practical implications: Everyday people’s life, practical activities, including marketing in social networks.DOI: http://dx.doi.org/10.12731/2218-7405-2013-9-51

Big Social Network Data and Sustainable Economic Development

Directory of Open Access Journals (Sweden)

Umit Can

2017-11-01

Full Text Available New information technologies have led to the rapid and effective growth of social networks. The amount of data produced by social networks has increased the value of the big data concept, which is one of the popular current phenomena. The immediate or unpredictable effects of a wide array of economic activities on large masses and the reactions to them can be measured by using social media platforms and big data methods. Thus, it would be extremely beneficial to analyze the harmful environmental and social impacts that are caused by unsustainable business applications. As social networks and big data are popular realms currently, their efficient use would be an important factor in sustainable economic development. Accurate analysis of people’s consumption habits and economic tendencies would provide significant advantages to companies. Moreover, unknown consumption factors that affect the economic preferences of individuals can be discovered and economic efficiency can be increased. This study shows that the numerous solution opportunities that are provided by social networks and big data have become significant tools in dynamic policy creation by companies and states, in solving problems related to women’s rights, the environment, and health.

Social Network Analysis and Mining to Monitor and Identify Problems with Large-Scale Information and Communication Technology Interventions.

Science.gov (United States)

da Silva, Aleksandra do Socorro; de Brito, Silvana Rossy; Vijaykumar, Nandamudi Lankalapalli; da Rocha, Cláudio Alex Jorge; Monteiro, Maurílio de Abreu; Costa, João Crisóstomo Weyl Albuquerque; Francês, Carlos Renato Lisboa

2016-01-01

The published literature reveals several arguments concerning the strategic importance of information and communication technology (ICT) interventions for developing countries where the digital divide is a challenge. Large-scale ICT interventions can be an option for countries whose regions, both urban and rural, present a high number of digitally excluded people. Our goal was to monitor and identify problems in interventions aimed at certification for a large number of participants in different geographical regions. Our case study is the training at the Telecentros.BR, a program created in Brazil to install telecenters and certify individuals to use ICT resources. We propose an approach that applies social network analysis and mining techniques to data collected from Telecentros.BR dataset and from the socioeconomics and telecommunications infrastructure indicators of the participants' municipalities. We found that (i) the analysis of interactions in different time periods reflects the objectives of each phase of training, highlighting the increased density in the phase in which participants develop and disseminate their projects; (ii) analysis according to the roles of participants (i.e., tutors or community members) reveals that the interactions were influenced by the center (or region) to which the participant belongs (that is, a community contained mainly members of the same region and always with the presence of tutors, contradicting expectations of the training project, which aimed for intense collaboration of the participants, regardless of the geographic region); (iii) the social network of participants influences the success of the training: that is, given evidence that the degree of the community member is in the highest range, the probability of this individual concluding the training is 0.689; (iv) the North region presented the lowest probability of participant certification, whereas the Northeast, which served municipalities with similar

Effects of deception in social networks.

Science.gov (United States)

Iñiguez, Gerardo; Govezensky, Tzipe; Dunbar, Robin; Kaski, Kimmo; Barrio, Rafael A

2014-09-07

Honesty plays a crucial role in any situation where organisms exchange information or resources. Dishonesty can thus be expected to have damaging effects on social coherence if agents cannot trust the information or goods they receive. However, a distinction is often drawn between prosocial lies ('white' lies) and antisocial lying (i.e. deception for personal gain), with the former being considered much less destructive than the latter. We use an agent-based model to show that antisocial lying causes social networks to become increasingly fragmented. Antisocial dishonesty thus places strong constraints on the size and cohesion of social communities, providing a major hurdle that organisms have to overcome (e.g. by evolving counter-deception strategies) in order to evolve large, socially cohesive communities. In contrast, white lies can prove to be beneficial in smoothing the flow of interactions and facilitating a larger, more integrated network. Our results demonstrate that these group-level effects can arise as emergent properties of interactions at the dyadic level. The balance between prosocial and antisocial lies may set constraints on the structure of social networks, and hence the shape of society as a whole. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Communication in Animal Social Networks

NARCIS (Netherlands)

Snijders, Lysanne; Naguib, Marc

2017-01-01

Animal social networks and animal communication networks are key disciplines for understanding animal social behavior, yet these disciplines remain poorly integrated. In this review, we show how communication and social networks are inherently linked, with social signals reflecting and affecting

Social networks and spreading of epidemics

Science.gov (United States)

Trimper, Steffen; Zheng, Dafang; Brandau, Marian

2004-05-01

Epidemiological processes are studied within a recently proposed social network model using the susceptible-infected-refractory dynamics (SIR) of an epidemic. Within the network model, a population of individuals may be characterized by H independent hierarchies or dimensions, each of which consists of groupings of individuals into layers of subgroups. Detailed numerical simulations reveals that for H > 1, the global spreading results regardless of the degree of homophily α of the individuals forming a social circle. For H = 1, a transition from a global to a local spread occurs as the population becomes decomposed into increasingly homophilous groups. Multiple dimensions in classifying individuals (nodes) thus make a society (computer network) highly susceptible to large scale outbreaks of infectious diseases (viruses). The SIR-model can be extended by the inclusion of waiting times resulting in modified distribution function of the recovered.

Social network in patient safety: Social media visibility

Directory of Open Access Journals (Sweden)

Azucena Santillán García

2011-11-01

Full Text Available Internet social network (social media is a powerful communication tool, and its use is expanding significantly. This paper seeks to know the current state of visibility in online social networks of active citizen talking about patient safety. This is an observational cross-sectional study whose target population is the websites Facebook, Twitter and Tuenti in Spain. By three consecutive cuts social profiles were found using the searching terms “seguridad+paciente” and “safety+patient”. There were found 5 profiles on Facebook that met the search criteria, 6 on Twitter and none were found on Tuenti. It is concluded that although there is evidence of the rise of social networking, citizen network involved in patient safety appears not to be significantly represented within the social networks examined.

Visualization of Social Networks

NARCIS (Netherlands)

Boertjes, E.M.; Kotterink, B.; Jager, E.J.

2011-01-01

Current visualizations of social networks are mostly some form of node-link diagram. Depending on the type of social network, this can be some treevisualization with a strict hierarchical structure or a more generic network visualization.

Group colocation behavior in technological social networks.

Directory of Open Access Journals (Sweden)

Chloë Brown

Full Text Available We analyze two large datasets from technological networks with location and social data: user location records from an online location-based social networking service, and anonymized telecommunications data from a European cellphone operator, in order to investigate the differences between individual and group behavior with respect to physical location. We discover agreements between the two datasets: firstly, that individuals are more likely to meet with one friend at a place they have not visited before, but tend to meet at familiar locations when with a larger group. We also find that groups of individuals are more likely to meet at places that their other friends have visited, and that the type of a place strongly affects the propensity for groups to meet there. These differences between group and solo mobility has potential technological applications, for example, in venue recommendation in location-based social networks.

Multilayer Social Networks

DEFF Research Database (Denmark)

Dickison, Mark; Magnani, Matteo; Rossi, Luca

social network systems, the evolution of interconnected social networks, and dynamic processes such as information spreading. A single real dataset is used to illustrate the concepts presented throughout the book, demonstrating both the practical utility and the potential shortcomings of the various...

Transaction costs and social networks in productivity measurement

DEFF Research Database (Denmark)

Henningsen, Geraldine; Henningsen, Arne; Henning, Christian H. C. A.

2015-01-01

. Hence, both the absolute productivity measures and, more importantly, the productivity ranking will be distorted. A major driver of transaction costs is poor access to information and contract enforcement assistance. Social networks often catalyse information exchange as well as generate trust...... and support. Hence, we use measures of a firm’s access to social networks as a proxy for the transaction costs the firm faces. We develop a microeconomic production model that takes into account transaction costs and networks. Using a data set of 384 Polish farms, we empirically estimate this model...... and compare different parametric, semiparametric, and nonparametric model specifications. Our results generally support our hypothesis. Especially, large trading networks and dense household networks have a positive influence on a farm’s productivity. Furthermore, our results indicate that transaction costs...

Maintenance of cultural diversity: social roles, social networks, and cognitive networks.

Science.gov (United States)

Abrams, Marshall

2014-06-01

Smaldino suggests that patterns that give rise to group-level cultural traits can also increase individual-level cultural diversity. I distinguish social roles and related social network structures and discuss ways in which each might maintain diversity. I suggest that cognitive analogs of "cohesion," a property of networks that helps maintenance of diversity, might mediate the effects of social roles on diversity.

Spectral Analysis Methods of Social Networks

Directory of Open Access Journals (Sweden)

P. G. Klyucharev

2017-01-01

Full Text Available Online social networks (such as Facebook, Twitter, VKontakte, etc. being an important channel for disseminating information are often used to arrange an impact on the social consciousness for various purposes - from advertising products or services to the full-scale information war thereby making them to be a very relevant object of research. The paper reviewed the analysis methods of social networks (primarily, online, based on the spectral theory of graphs. Such methods use the spectrum of the social graph, i.e. a set of eigenvalues of its adjacency matrix, and also the eigenvectors of the adjacency matrix.Described measures of centrality (in particular, centrality based on the eigenvector and PageRank, which reflect a degree of impact one or another user of the social network has. A very popular PageRank measure uses, as a measure of centrality, the graph vertices, the final probabilities of the Markov chain, whose matrix of transition probabilities is calculated on the basis of the adjacency matrix of the social graph. The vector of final probabilities is an eigenvector of the matrix of transition probabilities.Presented a method of dividing the graph vertices into two groups. It is based on maximizing the network modularity by computing the eigenvector of the modularity matrix.Considered a method for detecting bots based on the non-randomness measure of a graph to be computed using the spectral coordinates of vertices - sets of eigenvector components of the adjacency matrix of a social graph.In general, there are a number of algorithms to analyse social networks based on the spectral theory of graphs. These algorithms show very good results, but their disadvantage is the relatively high (albeit polynomial computational complexity for large graphs.At the same time it is obvious that the practical application capacity of the spectral graph theory methods is still underestimated, and it may be used as a basis to develop new methods.The work

Social exchange : Relations and networks

NARCIS (Netherlands)

Dijkstra, Jacob

2015-01-01

In this short paper, I review the literature on social exchange networks, with specific attention to theoretical and experimental research. I indicate how social exchange theory is rooted in general social theory and mention a few of its main links to social network analysis and empirical network

Social networks of older adults living with HIV in Finland.

Science.gov (United States)

Nobre, Nuno Ribeiro; Kylmä, Jari; Kirsi, Tapio; Pereira, Marco

2016-01-01

The aim of this study was to explore the social networks of older adults living with HIV. Interviews were conducted with nine individuals aged 50 or older living with HIV in Helsinki, Finland. Analysis of transcripts was analysed by inductive qualitative content analysis. Results indicated that these participants' networks tended to be large, including those both aware and unaware of the participants' health status. Analysis identified three main themes: large multifaceted social networks, importance of a support group, and downsizing of social networks. Support received appeared to be of great importance in coping with their health condition, especially since the time of diagnosis. Friends and family were the primary source of informal support. The majority of participants relied mostly on friends, some of whom were HIV-positive. Formal support came primarily from the HIV organisation's support group. In this study group, non-disclosure did not impact participants' well-being. In years to come, social networks of older adults living with HIV may shrink due to personal reasons other than HIV-disclosure. What is of primary importance is that healthcare professionals become knowledgeable about psychosocial issues of older adults living with HIV, identifying latent problems and developing adequate interventions in the early stages of the disease; this would help prevent social isolation and foster successful ageing with HIV.

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

Model of community emergence in weighted social networks

Science.gov (United States)

Kumpula, J. M.; Onnela, J.-P.; Saramäki, J.; Kertész, J.; Kaski, K.

2009-04-01

Over the years network theory has proven to be rapidly expanding methodology to investigate various complex systems and it has turned out to give quite unparalleled insight to their structure, function, and response through data analysis, modeling, and simulation. For social systems in particular the network approach has empirically revealed a modular structure due to interplay between the network topology and link weights between network nodes or individuals. This inspired us to develop a simple network model that could catch some salient features of mesoscopic community and macroscopic topology formation during network evolution. Our model is based on two fundamental mechanisms of network sociology for individuals to find new friends, namely cyclic closure and focal closure, which are mimicked by local search-link-reinforcement and random global attachment mechanisms, respectively. In addition we included to the model a node deletion mechanism by removing all its links simultaneously, which corresponds for an individual to depart from the network. Here we describe in detail the implementation of our model algorithm, which was found to be computationally efficient and produce many empirically observed features of large-scale social networks. Thus this model opens a new perspective for studying such collective social phenomena as spreading, structure formation, and evolutionary processes.

Dynamics of adolescent friendship networks and smoking behavior : Social network analyses in six European countries

NARCIS (Netherlands)

Mercken, Liesbeth; Snijders, Tom A. B.; Steglich, Christian; de Vries, H.

The co-evolution of adolescents' friendship networks and their smoking behavior is examined in a large sample across six European countries. Selection and influence processes are disentangled using new methods of social network analysis that enable alternative selection mechanisms to be controlled

On Deep Learning for Trust-Aware Recommendations in Social Networks.

Science.gov (United States)

Deng, Shuiguang; Huang, Longtao; Xu, Guandong; Wu, Xindong; Wu, Zhaohui

2017-05-01

With the emergence of online social networks, the social network-based recommendation approach is popularly used. The major benefit of this approach is the ability of dealing with the problems with cold-start users. In addition to social networks, user trust information also plays an important role to obtain reliable recommendations. Although matrix factorization (MF) becomes dominant in recommender systems, the recommendation largely relies on the initialization of the user and item latent feature vectors. Aiming at addressing these challenges, we develop a novel trust-based approach for recommendation in social networks. In particular, we attempt to leverage deep learning to determinate the initialization in MF for trust-aware social recommendations and to differentiate the community effect in user's trusted friendships. A two-phase recommendation process is proposed to utilize deep learning in initialization and to synthesize the users' interests and their trusted friends' interests together with the impact of community effect for recommendations. We perform extensive experiments on real-world social network data to demonstrate the accuracy and effectiveness of our proposed approach in comparison with other state-of-the-art methods.

Social exchange: Relations and networks

OpenAIRE

Dijkstra, Jacob

2015-01-01

In this short paper, I review the literature on social exchange networks, with specific attention to theoretical and experimental research. I indicate how social exchange theory is rooted in general social theory and mention a few of its main links to social network analysis and empirical network research. The paper provides an accessible entry into the literature on social exchange.

Myths on Bi-direction Communication of Web 2.0 Based Social Networks: Is Social Network Truly Interactive?

Science.gov (United States)

2011-03-10

more and more social interactions are happening on the on-line. Especially recent uptake of the social network sites (SNSs), such as Facebook (http...Smart phones • Live updates within social networks • Facebook & Twitters Solution: WebMon for Risk Management Need for New WebMon for Social Networks ...Title: Myths on bi-direction communication of Web 2.0 based social networks : Is social network truly interactive

Analyzing, Modeling, and Simulation for Human Dynamics in Social Network

Directory of Open Access Journals (Sweden)

Yunpeng Xiao

2012-01-01

Full Text Available This paper studies the human behavior in the top-one social network system in China (Sina Microblog system. By analyzing real-life data at a large scale, we find that the message releasing interval (intermessage time obeys power law distribution both at individual level and at group level. Statistical analysis also reveals that human behavior in social network is mainly driven by four basic elements: social pressure, social identity, social participation, and social relation between individuals. Empirical results present the four elements' impact on the human behavior and the relation between these elements. To further understand the mechanism of such dynamic phenomena, a hybrid human dynamic model which combines “interest” of individual and “interaction” among people is introduced, incorporating the four elements simultaneously. To provide a solid evaluation, we simulate both two-agent and multiagent interactions with real-life social network topology. We achieve the consistent results between empirical studies and the simulations. The model can provide a good understanding of human dynamics in social network.

Social contagions on correlated multiplex networks

Science.gov (United States)

Wang, Wei; Cai, Meng; Zheng, Muhua

2018-06-01

The existence of interlayer degree correlations has been disclosed by abundant multiplex network analysis. However, how they impose on the dynamics of social contagions are remain largely unknown. In this paper, we propose a non-Markovian social contagion model in multiplex networks with inter-layer degree correlations to delineate the behavior spreading, and develop an edge-based compartmental (EBC) theory to describe the model. We find that multiplex networks promote the final behavior adoption size. Remarkably, it can be observed that the growth pattern of the final behavior adoption size, versus the behavioral information transmission probability, changes from discontinuous to continuous once decreasing the behavior adoption threshold in one layer. We finally unravel that the inter-layer degree correlations play a role on the final behavior adoption size but have no effects on the growth pattern, which is coincidence with our prediction by using the suggested theory.

Entropy of dynamical social networks

Science.gov (United States)

Zhao, Kun; Karsai, Marton; Bianconi, Ginestra

2012-02-01

Dynamical social networks are evolving rapidly and are highly adaptive. Characterizing the information encoded in social networks is essential to gain insight into the structure, evolution, adaptability and dynamics. Recently entropy measures have been used to quantify the information in email correspondence, static networks and mobility patterns. Nevertheless, we still lack methods to quantify the information encoded in time-varying dynamical social networks. In this talk we present a model to quantify the entropy of dynamical social networks and use this model to analyze the data of phone-call communication. We show evidence that the entropy of the phone-call interaction network changes according to circadian rhythms. Moreover we show that social networks are extremely adaptive and are modified by the use of technologies such as mobile phone communication. Indeed the statistics of duration of phone-call is described by a Weibull distribution and is significantly different from the distribution of duration of face-to-face interactions in a conference. Finally we investigate how much the entropy of dynamical social networks changes in realistic models of phone-call or face-to face interactions characterizing in this way different type human social behavior.

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.

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.

Attachment and social networks.

Science.gov (United States)

Gillath, Omri; C Karantzas, Gery; Lee, Juwon

2018-02-21

The current review covers two lines of research linking attachment and social networks. One focuses on attachment networks (the people who fulfill one's attachment needs), examining composition and age-related differences pertaining to these networks. The other line integrates attachment with social network analysis to investigate how individual differences in adult attachment are associated with the management and characteristics (e.g., density, multiplexity, and centrality) of people's social networks. We show that most people's attachment networks are small and hierarchical, with one figure being the primary attachment figure (often a mother or romantic partner, depending on age). Furthermore, attachment style predicts network characteristics and management, such that insecurity is associated with less closeness, multiplexity, centrality, and poorer management (less maintenance, more dissolution). Copyright © 2018 Elsevier Ltd. All rights reserved.

Social inheritance can explain the structure of animal social networks

Science.gov (United States)

Ilany, Amiyaal; Akçay, Erol

2016-01-01

The social network structure of animal populations has major implications for survival, reproductive success, sexual selection and pathogen transmission of individuals. But as of yet, no general theory of social network structure exists that can explain the diversity of social networks observed in nature, and serve as a null model for detecting species and population-specific factors. Here we propose a simple and generally applicable model of social network structure. We consider the emergence of network structure as a result of social inheritance, in which newborns are likely to bond with maternal contacts, and via forming bonds randomly. We compare model output with data from several species, showing that it can generate networks with properties such as those observed in real social systems. Our model demonstrates that important observed properties of social networks, including heritability of network position or assortative associations, can be understood as consequences of social inheritance. PMID:27352101

Seven Deadliest Social Network Attacks

CERN Document Server

Timm, Carl

2010-01-01

Do you need to keep up with the latest hacks, attacks, and exploits effecting social networks? Then you need Seven Deadliest Social Network Attacks. This book pinpoints the most dangerous hacks and exploits specific to social networks like Facebook, Twitter, and MySpace, laying out the anatomy of these attacks including how to make your system more secure. You will discover the best ways to defend against these vicious hacks with step-by-step instruction and learn techniques to make your computer and network impenetrable. Attacks detailed in this book include: Social Networking Infrastruct

Next Generation Social Networks

DEFF Research Database (Denmark)

Sørensen, Lene Tolstrup; Skouby, Knud Erik

2008-01-01

different online networks for communities of people who share interests or individuals who presents themselves through user produced content is what makes up the social networking of today. The purpose of this paper is to discuss perceived user requirements to the next generation social networks. The paper...

Twitter=quitter? An analysis of Twitter quit smoking social networks.

Science.gov (United States)

Prochaska, Judith J; Pechmann, Cornelia; Kim, Romina; Leonhardt, James M

2012-07-01

Widely popular, Twitter, a free social networking and micro-blogging service, offers potential for health promotion. This study examined the activity of Twitter quit smoking social network accounts. A cross-sectional analysis identified 153 activated Twitter quit smoking accounts dating back to 2007 and examined recent account activity for the month of August 2010. The accounts had a median of 155 followers and 82 total tweets per account; 49% of accounts had >100 tweets. Posted content was largely inconsistent with clinical guidelines; 48% linked to commercial sites for quitting smoking and 43% had tweets on e-cigarettes. In August 2010, 81 of the accounts (53%) were still active. Though popular for building quit smoking social networks, many of the Twitter accounts were no longer active, and tweet content was largely inconsistent with clinical guidelines. Future research is needed to examine the effectiveness of Twitter for supporting smoking cessation.

An agent-based model of centralized institutions, social network technology, and revolution.

Science.gov (United States)

Makowsky, Michael D; Rubin, Jared

2013-01-01

This paper sheds light on the general mechanisms underlying large-scale social and institutional change. We employ an agent-based model to test the impact of authority centralization and social network technology on preference falsification and institutional change. We find that preference falsification is increasing with centralization and decreasing with social network range. This leads to greater cascades of preference revelation and thus more institutional change in highly centralized societies and this effect is exacerbated at greater social network ranges. An empirical analysis confirms the connections that we find between institutional centralization, social radius, preference falsification, and institutional change.

Networks in Social Policy Problems

Science.gov (United States)

Vedres, Balázs; Scotti, Marco

2012-08-01

1. Introduction M. Scotti and B. Vedres; Part I. Information, Collaboration, Innovation: The Creative Power of Networks: 2. Dissemination of health information within social networks C. Dhanjal, S. Blanchemanche, S. Clemençon, A. Rona-Tas and F. Rossi; 3. Scientific teams and networks change the face of knowledge creation S. Wuchty, J. Spiro, B. F. Jones and B. Uzzi; 4. Structural folds: the innovative potential of overlapping groups B. Vedres and D. Stark; 5. Team formation and performance on nanoHub: a network selection challenge in scientific communities D. Margolin, K. Ognyanova, M. Huang, Y. Huang and N. Contractor; Part II. Influence, Capture, Corruption: Networks Perspectives on Policy Institutions: 6. Modes of coordination of collective action: what actors in policy making? M. Diani; 7. Why skewed distributions of pay for executives is the cause of much grief: puzzles and few answers so far B. Kogut and J.-S. Yang; 8. Networks of institutional capture: a case of business in the State apparatus E. Lazega and L. Mounier; 9. The social and institutional structure of corruption: some typical network configurations of corruption transactions in Hungary Z. Szántó, I. J. Tóth and S. Varga; Part III. Crisis, Extinction, World System Change: Network Dynamics on a Large Scale: 10. How creative elements help the recovery of networks after crisis: lessons from biology A. Mihalik, A. S. Kaposi, I. A. Kovács, T. Nánási, R. Palotai, Á. Rák, M. S. Szalay-Beko and P. Csermely; 11. Networks and globalization policies D. R. White; 12. Network science in ecology: the structure of ecological communities and the biodiversity question A. Bodini, S. Allesina and C. Bondavalli; 13. Supply security in the European natural gas pipeline network M. Scotti and B. Vedres; 14. Conclusions and outlook A.-L. Barabási; Index.

Social network indices in the Generations and Gender Survey: An appraisal

Directory of Open Access Journals (Sweden)

Pearl A. Dykstra

2016-06-01

Full Text Available Background: In this contribution we critically appraise the social network indices in the Generations and Gender Survey (GGS. Objective: After discussing the rationale for including social network indices in the GGS, we provide descriptive information on social network characteristics and an overview of substantive questions that have been addressed using GGS social network data: antecedents and consequences of demographic behaviour, care, and differences in well-being. We identify topics that have received relatively little attention in GGS research so far, despite the availability of novel and appropriate social network data. We end with a discussion of what is unique about the social network indices in the GGS. Methods: The descriptive information on social network characteristics is based on empirical analyses of GGS data, and an experimental pilot study. The overview of GGS research using social network indices is based on a library search. The identification of what is unique about the social network indices in the GGS is based on a comparison with the European Quality of Life Survey (EQLS, the Survey of Health, Ageing and Retirement (SHARE, and the International Social Survey Program (ISSP. Results: Results show a high representation of family members in the social networks, and confirm the adequacy of using a cap of five names for network-generating questions. GGS research using the social network indices has largely focused on determinants of fertility behaviour, intergenerational linkages in families, and downward care transfers. Conclusions: Topics that have received relatively little attention are demographic behaviours other than those related to parenthood, upward transfers of practical support, ties with siblings, and stepfamily ties. Social network indices in the GGS show a high degree of overlap with those in other international surveys. The unique features are the inventory of family ties ever born and still living, and the

Social network sites: Indispensable or optional social tools?

DEFF Research Database (Denmark)

Shklovski, Irina

2012-01-01

Much research has enumerated potential benefits of online social network sites. Given the pervasiveness of these sites and the numbers of people that use them daily, both re-search and media tend to make the assumption that social network sites have become indispensible to their users. Based...... on the analysis of qualitative data from users of social network sites in Russia and Kazakhstan, this paper consid-ers under what conditions social network sites can become indispensable to their users and when these technologies remain on the periphery of life despite fulfilling useful func-tions. For some...... respondents, these sites had become indis-pensable tools as they were integrated into everyday rou-tines of communicating with emotionally important and proximal contacts and were often used for coordination of offline activities. For others social network sites remained spaces where they occasionally visited...

How Many "Friends" Do You Need? Teaching Students How to Network Using Social Media

Science.gov (United States)

Sacks, Michael Alan; Graves, Nikki

2012-01-01

Student reliance on social media is undeniable. However, while we largely regard social media as a new phenomena, the concepts underlying it come directly from social network theory in sociology and organizational behavior. In this article, the authors examine how the social network concepts of size, quality, complexity, diffusion, and distance…

Social inertia and diversity in collaboration networks

Science.gov (United States)

Ramasco, J. J.

2007-04-01

Random graphs are useful tools to study social interactions. In particular, the use of weighted random graphs allows to handle a high level of information concerning which agents interact and in which degree the interactions take place. Taking advantage of this representation, we recently defined a magnitude, the Social Inertia, that measures the eagerness of agents to keep ties with previous partners. To study this magnitude, we used collaboration networks that are specially appropriate to obtain valid statitical results due to the large size of publically available databases. In this work, I study the Social Inertia in two of these empirical networks, IMDB movie database and condmat. More specifically, I focus on how the Inertia relates to other properties of the graphs, and show that the Inertia provides information on how the weight of neighboring edges correlates. A social interpretation of this effect is also offered.

Modeling social networks in geographic space: approach and empirical application

NARCIS (Netherlands)

Arentze, T.A.; Berg, van den P.E.W.; Timmermans, H.J.P.

2012-01-01

Social activities are responsible for a large proportion of travel demands of individuals. Modeling of the social network of a studied population offers a basis to predict social travel in a more comprehensive way than currently is possible. In this paper we develop a method to generate a whole

Enterprise Social Networks

DEFF Research Database (Denmark)

Winkler, Till J.; Trier, Matthias

2017-01-01

Enterprise Social Networks (ESNs), d. h. Informationssysteme, die die Vernetzung von Mitarbeitern in Unternehmen fördern sollen, sind in verschiedenen Varianten und unter verschiedenen Bezeichnungen (etwa Enterprise Social Media, Corporate Social Software, Social Business oder Enterprise 2...

A Social Network Approach Reveals Associations between Mouse Social Dominance and Brain Gene Expression

Science.gov (United States)

So, Nina; Franks, Becca; Lim, Sean; Curley, James P.

2015-01-01

Modelling complex social behavior in the laboratory is challenging and requires analyses of dyadic interactions occurring over time in a physically and socially complex environment. In the current study, we approached the analyses of complex social interactions in group-housed male CD1 mice living in a large vivarium. Intensive observations of social interactions during a 3-week period indicated that male mice form a highly linear and steep dominance hierarchy that is maintained by fighting and chasing behaviors. Individual animals were classified as dominant, sub-dominant or subordinate according to their David’s Scores and I& SI ranking. Using a novel dynamic temporal Glicko rating method, we ascertained that the dominance hierarchy was stable across time. Using social network analyses, we characterized the behavior of individuals within 66 unique relationships in the social group. We identified two individual network metrics, Kleinberg’s Hub Centrality and Bonacich’s Power Centrality, as accurate predictors of individual dominance and power. Comparing across behaviors, we establish that agonistic, grooming and sniffing social networks possess their own distinctive characteristics in terms of density, average path length, reciprocity out-degree centralization and out-closeness centralization. Though grooming ties between individuals were largely independent of other social networks, sniffing relationships were highly predictive of the directionality of agonistic relationships. Individual variation in dominance status was associated with brain gene expression, with more dominant individuals having higher levels of corticotropin releasing factor mRNA in the medial and central nuclei of the amygdala and the medial preoptic area of the hypothalamus, as well as higher levels of hippocampal glucocorticoid receptor and brain-derived neurotrophic factor mRNA. This study demonstrates the potential and significance of combining complex social housing and intensive

A Social Network Approach Reveals Associations between Mouse Social Dominance and Brain Gene Expression.

Directory of Open Access Journals (Sweden)

Nina So

Full Text Available Modelling complex social behavior in the laboratory is challenging and requires analyses of dyadic interactions occurring over time in a physically and socially complex environment. In the current study, we approached the analyses of complex social interactions in group-housed male CD1 mice living in a large vivarium. Intensive observations of social interactions during a 3-week period indicated that male mice form a highly linear and steep dominance hierarchy that is maintained by fighting and chasing behaviors. Individual animals were classified as dominant, sub-dominant or subordinate according to their David's Scores and I& SI ranking. Using a novel dynamic temporal Glicko rating method, we ascertained that the dominance hierarchy was stable across time. Using social network analyses, we characterized the behavior of individuals within 66 unique relationships in the social group. We identified two individual network metrics, Kleinberg's Hub Centrality and Bonacich's Power Centrality, as accurate predictors of individual dominance and power. Comparing across behaviors, we establish that agonistic, grooming and sniffing social networks possess their own distinctive characteristics in terms of density, average path length, reciprocity out-degree centralization and out-closeness centralization. Though grooming ties between individuals were largely independent of other social networks, sniffing relationships were highly predictive of the directionality of agonistic relationships. Individual variation in dominance status was associated with brain gene expression, with more dominant individuals having higher levels of corticotropin releasing factor mRNA in the medial and central nuclei of the amygdala and the medial preoptic area of the hypothalamus, as well as higher levels of hippocampal glucocorticoid receptor and brain-derived neurotrophic factor mRNA. This study demonstrates the potential and significance of combining complex social housing

A Markov chain model for image ranking system in social networks

Science.gov (United States)

Zin, Thi Thi; Tin, Pyke; Toriu, Takashi; Hama, Hiromitsu

2014-03-01

In today world, different kinds of networks such as social, technological, business and etc. exist. All of the networks are similar in terms of distributions, continuously growing and expanding in large scale. Among them, many social networks such as Facebook, Twitter, Flickr and many others provides a powerful abstraction of the structure and dynamics of diverse kinds of inter personal connection and interaction. Generally, the social network contents are created and consumed by the influences of all different social navigation paths that lead to the contents. Therefore, identifying important and user relevant refined structures such as visual information or communities become major factors in modern decision making world. Moreover, the traditional method of information ranking systems cannot be successful due to their lack of taking into account the properties of navigation paths driven by social connections. In this paper, we propose a novel image ranking system in social networks by using the social data relational graphs from social media platform jointly with visual data to improve the relevance between returned images and user intentions (i.e., social relevance). Specifically, we propose a Markov chain based Social-Visual Ranking algorithm by taking social relevance into account. By using some extensive experiments, we demonstrated the significant and effectiveness of the proposed social-visual ranking method.

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.

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

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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…

Social Networks and Health.

Science.gov (United States)

Perdiaris, Christos; Chardalias, Konstantinos; Magita, Andrianna; Mechili, Aggelos E; Diomidous, Marianna

2015-01-01

Nowadays the social networks have been developed into an advanced communications tool, which is important for all people to contact each other. These specific networks do offer lots of options as well as plenty of advantages and disadvantages. The social websites are many in number and titles, such as the facebook, the twitter, the bandoo etc. One of the most important function-mechanisms for the social network websites, are the marketing tools. The future goal is suggested to be the evolution of these programs. The development of these applications, which is going to lead into a new era for the social digital communication between the internet users, all around the globe.

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

Signed Networks in Social Media

OpenAIRE

Leskovec, Jure; Huttenlocher, Daniel; Kleinberg, Jon

2010-01-01

Relations between users on social media sites often reflect a mixture of positive (friendly) and negative (antagonistic) interactions. In contrast to the bulk of research on social networks that has focused almost exclusively on positive interpretations of links between people, we study how the interplay between positive and negative relationships affects the structure of on-line social networks. We connect our analyses to theories of signed networks from social psychology. We find that the c...

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.

Online Advertising in Social Networks

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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.

Social Networking Sites in Education

OpenAIRE

Suková, Lenka

2010-01-01

Diploma thesis deals with social networking sites and their use in education. Thesis is divided into two general parts. The first part deals with theory of learning; Bloom's taxonomy of educational objectives and new educational theory based on learning in networks -- Connectivism. After that thesis focuses on the definition of social networking sites, introduction of some of the best known social networking sites and examples of their use in foreign and domestic educational practice. The sec...

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.

Complex modular structure of large-scale brain networks

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Valencia, M.; Pastor, M. A.; Fernández-Seara, M. A.; Artieda, J.; Martinerie, J.; Chavez, M.

2009-06-01

Modular structure is ubiquitous among real-world networks from related proteins to social groups. Here we analyze the modular organization of brain networks at a large scale (voxel level) extracted from functional magnetic resonance imaging signals. By using a random-walk-based method, we unveil the modularity of brain webs and show modules with a spatial distribution that matches anatomical structures with functional significance. The functional role of each node in the network is studied by analyzing its patterns of inter- and intramodular connections. Results suggest that the modular architecture constitutes the structural basis for the coexistence of functional integration of distant and specialized brain areas during normal brain activities at rest.

Long-Term Evolution of Email Networks: Statistical Regularities, Predictability and Stability of Social Behaviors.

Science.gov (United States)

Godoy-Lorite, Antonia; Guimerà, Roger; Sales-Pardo, Marta

2016-01-01

In social networks, individuals constantly drop ties and replace them by new ones in a highly unpredictable fashion. This highly dynamical nature of social ties has important implications for processes such as the spread of information or of epidemics. Several studies have demonstrated the influence of a number of factors on the intricate microscopic process of tie replacement, but the macroscopic long-term effects of such changes remain largely unexplored. Here we investigate whether, despite the inherent randomness at the microscopic level, there are macroscopic statistical regularities in the long-term evolution of social networks. In particular, we analyze the email network of a large organization with over 1,000 individuals throughout four consecutive years. We find that, although the evolution of individual ties is highly unpredictable, the macro-evolution of social communication networks follows well-defined statistical patterns, characterized by exponentially decaying log-variations of the weight of social ties and of individuals' social strength. At the same time, we find that individuals have social signatures and communication strategies that are remarkably stable over the scale of several years.

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 ...

Conceptualizing of Social Networking Sites

OpenAIRE

J. S. Sodhi; Shilpi Sharma

2012-01-01

People often move to their friends, families and colleagues when they feel urge and having doubts or queries to solve. Participation in social networking site has dramatically increased in recent years. Many social networking sites boost with million of members using their network on regular basis to communicate, share , create and collaborate with others. In this paper we explore the phenomenon of using social networking site to trace a link of the search from the community of users for bett...

Social Network Analysis and informal trade

DEFF Research Database (Denmark)

Walther, Olivier

networks can be applied to better understand informal trade in developing countries, with a particular focus on Africa. The paper starts by discussing some of the fundamental concepts developed by social network analysis. Through a number of case studies, we show how social network analysis can...... illuminate the relevant causes of social patterns, the impact of social ties on economic performance, the diffusion of resources and information, and the exercise of power. The paper then examines some of the methodological challenges of social network analysis and how it can be combined with other...... approaches. The paper finally highlights some of the applications of social network analysis and their implications for trade policies....

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

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

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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.

Social networking services: technologies and applications

OpenAIRE

Puzyrnyy, Oleksandr

2011-01-01

Puzyrnyy, Oleksandr. 2011. Social networking services: technologies and applications. Bachelor's Thesis. Kemi-Tornio University of Applied Sciences. Business and Culture. Pages 52. The aim of this thesis is to describe the concept of social networking, its technological base, business opportunities and future perspectives. The study discovers how social networks are made and which different purposes they might have. In addition, social networking is viewed as a part of business strategy o...

Brand Marketing Model on Social Networks

Directory of Open Access Journals (Sweden)

Jolita Jezukevičiūtė

2014-04-01

Full Text Available The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalysis of a single case study revealed a brand marketingsocial networking tools that affect consumers the most. Basedon information analysis and methodological studies, develop abrand marketing model on social networks.

Social Sensor Analytics: Making Sense of Network Models in Social Media

Energy Technology Data Exchange (ETDEWEB)

Dowling, Chase P.; Harrison, Joshua J.; Sathanur, Arun V.; Sego, Landon H.; Corley, Courtney D.

2015-07-27

Social networks can be thought of as noisy sensor networks mapping real world information to the web. Owing to the extensive body of literature in sensor network analysis, this work sought to apply several novel and traditional methods in sensor network analysis for the purposes of efficiently interrogating social media data streams from raw data. We carefully revisit our definition of a social media signal from previous work both in terms of time-varying features within the data and the networked nature of the medium. Further, we detail our analysis of global patterns in Twitter over the months of November 2013 and June 2014, detect and categorize events, and illustrate how these analyses can be used to inform graph-based models of Twitter, namely using a recent network influence model called PhySense: similar to PageRank but tuned to behavioral analysis by leveraging a sociologically inspired probabilistic model. We ultimately identify forms of information dissemination via analysis of time series and dynamic graph spectra and corroborate these findings through manual investigation of the data as a requisite step in modeling the diffusion process with PhySense. We hope to sufficiently characterize global behavior in a medium such as Twitter as a means of learning global model parameters one may use to predict or simulate behavior on a large scale. We have made our time series and dynamic graph analytical code available via a GitHub repository https://github.com/cpatdowling/salsa and our data are available upon request.

Sentiment Propagation in Social Networks: A Case Study in LiveJournal

Science.gov (United States)

Zafarani, Reza; Cole, William D.; Liu, Huan

Social networking websites have facilitated a new style of communication through blogs, instant messaging, and various other techniques. Through collaboration, millions of users participate in millions of discussions every day. However, it is still difficult to determine the extent to which such discussions affect the emotions of the participants. We surmise that emotionally-oriented discussions may affect a given user's general emotional bent and be reflected in other discussions he or she may initiate or participate in. It is in this way that emotion (or sentiment) may propagate through a network. In this paper, we analyze sentiment propagation in social networks, review the importance and challenges of such a study, and provide methodologies for measuring this kind of propagation. A case study has been conducted on a large dataset gathered from the LiveJournal social network. Experimental results are promising in revealing some aspects of the sentiment propagation taking place in social networks.

Social Network Perspective: Model of Student Knowledge Sharing On Social Network Media

OpenAIRE

Bentar Priyopradono; Danny Manongga; Wiranto H. Utomo

2012-01-01

Recently, the role and development of information technology especially the internet, gives impact and influence in social relationship especially for social network site services users. The impact and influence the use of Internet which is related to exchange information and knowledge sharing still become one of the interesting topics to be researched. Now, the use of social media network by students are the best way to them to increase their knowledge as communication media such as, exchang...

Invited Commentary: Evolution of Social Networks, Health, and the Role of Epidemiology.

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Aiello, Allison E

2017-06-01

Almost 40 years ago, Berkman and Syme demonstrated that social networks were related to the risk of early mortality (Am J Epidemiol. 1979;109(2):186-204). Their study was highly innovative because they directly measured and quantified social networks in a large prospective population-based survey with mortality follow-up. The results of the study showed robust network gradients, whereby those with fewer networks and weaker social ties had significantly higher mortality rates. The important influence of social networks that Berkman and Syme noted many years ago is likely to heighten in the future, as demographic characteristics shift and individuals become more inclined to socialize through online platforms instead of real-world interactions. Berkman and Syme's research in 1979 continues to play a key role in shaping recent efforts to uncover the influence of social networks on health. Looking back on their findings may help epidemiologists better understand the importance of both online and offline networks for population health today. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Using Social Network Research in HRM

DEFF Research Database (Denmark)

Kaše, Robert; King, Zella; Minbaeva, Dana

2013-01-01

; the impact of social networking sites on perceptions of relationships; and ethical issues in organizational network analysis, we propose specific suggestions to bring social network perspectives closer to HRM researchers and practitioners and rebalance our attention to people and to their relationships.......The article features a conversation between Rob Cross and Martin Kilduff about organizational network analysis in research and practice. It demonstrates the value of using social network perspectives in HRM. Drawing on the discussion about managing personal networks; managing the networks of others...

Mobile social networking an innovative approach

CERN Document Server

Zhang, Daqing

2014-01-01

The use of contextually aware, pervasive, distributed computing, and sensor networks to bridge the gap between the physical and online worlds is the basis of mobile social networking. This book shows how applications can be built to provide mobile social networking, the research issues that need to be solved to enable this vision, and how mobile social networking can be used to provide computational intelligence that will improve daily life. With contributions from the fields of sociology, computer science, human-computer interaction and design, this book demonstrates how mobile social networks can be inferred from users' physical interactions both with the environment and with others, as well as how users behave around them and how their behavior differs on mobile vs. traditional online social networks.

Staying Safe on Social Network Sites

Science.gov (United States)

... Tips Security Tip (ST06-003) Staying Safe on Social Networking Sites Original release date: January 26, 2011 | Last revised: ... so you should take certain precautions. What are social networking sites? Social networking sites, sometimes referred to as "friend- ...

One Health in social networks and social media.

Science.gov (United States)

Mekaru, S R; Brownstein, J S

2014-08-01

In the rapidly evolving world of social media, social networks, mobile applications and citizen science, online communities can develop organically and separately from larger or more established organisations. The One Health online community is experiencing expansion from both the bottom up and the top down. In this paper, the authors review social media's strengths and weaknesses, earlier work examining Internet resources for One Health, the current state of One Health in social media (e.g. Facebook, Twitter, YouTube) and online social networking sites (e.g. LinkedIn and ResearchGate), as well as social media in One Health-related citizen science projects. While One Health has a fairly strong presence on websites, its social media presence is more limited and has an uneven geographic distribution. In work following the Stone Mountain Meeting,the One Health Global Network Task Force Report recommended the creation of an online community of practice. Professional social networks as well as the strategic use of social media should be employed in this effort. Finally, One Health-related research projects using volunteers (citizen science) often use social media to enhance their recruitment. Including these researchers in a community of practitioners would take full advantage of their existing social media presence. In conclusion, the interactive nature of social media, combined with increasing global Internet access, provides the One Health community with opportunities to meaningfully expand their community and promote their message.

Brand marketing model on social networks

OpenAIRE

Jezukevičiūtė, Jolita; Davidavičienė, Vida

2014-01-01

Paper analyzes the brand and its marketing solutions on social networks. This analysis led to the creation of improved brand marketing model on social networks, which will contribute to the rapid and cheap organization brand recognition, increase competitive advantage and enhance consumer loyalty. Therefore, the brand and a variety of social networks are becoming a hot research area for brand marketing model on social networks. The world‘s most successful brand marketing models exploratory an...

Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation.

Science.gov (United States)

Hu, Hongzhi; Mao, Huajuan; Hu, Xiaohua; Hu, Feng; Sun, Xuemin; Jing, Zaiping; Duan, Yunsuo

2015-01-01

Due to the extensive social influence, public health emergency has attracted great attention in today's society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency management, among which a good prediction of information dissemination in social networks is necessary for estimating the event's social impacts and making a proper strategy. However, information dissemination is largely affected by complex interactive activities and group behaviors in social network; the existing methods and models are limited to achieve a satisfactory prediction result due to the open changeable social connections and uncertain information processing behaviors. ACP (artificial societies, computational experiments, and parallel execution) provides an effective way to simulate the real situation. In order to obtain better information dissemination prediction in social networks, this paper proposes an intelligent computation method under the framework of TDF (Theory-Data-Feedback) based on ACP simulation system which was successfully applied to the analysis of A (H1N1) Flu emergency.

Multiple effect of social influence on cooperation in interdependent network games

Science.gov (United States)

Jiang, Luo-Luo; Li, Wen-Jing; Wang, Zhen

2015-10-01

The social influence exists widely in the human society, where individual decision-making process (from congressional election to electronic commerce) may be affected by the attitude and behavior of others belonging to different social networks. Here, we couple the snowdrift (SD) game and the prisoner’s dilemma (PD) game on two interdependent networks, where strategies in both games are associated by social influence to mimick the majority rule. More accurately, individuals’ strategies updating refers to social learning (based on payoff difference) and above-mentioned social influence (related with environment of interdependent group), which is controlled by social influence strength s. Setting s = 0 decouples the networks and returns the traditional network game; while its increase involves the interactions between networks. By means of numerous Monte Carlo simulations, we find that such a mechanism brings multiple influence to the evolution of cooperation. Small s leads to unequal cooperation level in both games, because social learning is still the main updating rule for most players. Though intermediate and large s guarantees the synchronized evolution of strategy pairs, cooperation finally dies out and reaches a completely dominance in both cases. Interestingly, these observations are attributed to the expansion of cooperation clusters. Our work may provide a new understanding to the emergence of cooperation in intercorrelated social systems.

Social disadvantage and borderline personality disorder: A study of social networks.

Science.gov (United States)

Beeney, Joseph E; Hallquist, Michael N; Clifton, Allan D; Lazarus, Sophie A; Pilkonis, Paul A

2018-01-01

Examining differences in social integration, social support, and relationship characteristics in social networks may be critical for understanding the character and costs of the social difficulties experienced of borderline personality disorder (BPD). We conducted an ego-based (self-reported, individual) social network analysis of 142 participants recruited from clinical and community sources. Each participant listed the 30 most significant people (called alters) in their social network, then rated each alter in terms of amount of contact, social support, attachment strength and negative interactions. In addition, measures of social integration were determined using participant's report of the connection between people in their networks. BPD was associated with poorer social support, more frequent negative interactions, and less social integration. Examination of alter-by-BPD interactions indicated that whereas participants with low BPD symptoms had close relationships with people with high centrality within their networks, participants with high BPD symptoms had their closest relationships with people less central to their networks. The results suggest that individuals with BPD are at a social disadvantage: Those with whom they are most closely linked (including romantic partners) are less socially connected (i.e., less central) within their social network. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Social multimedia signals a signal processing approach to social network phenomena

CERN Document Server

Roy, Suman Deb

2014-01-01

This book provides a comprehensive coverage of the state-of-the-art in understanding media popularity and trends in online social networks through social multimedia signals. With insights from the study of popularity and sharing patterns of online media, trend spread in social media, social network analysis for multimedia and visualizing diffusion of media in online social networks. In particular, the book will address the following important issues: Understanding social network phenomena from a signal processing point of view; The existence and popularity of multimedia as shared and social me

The Possibilities of Network Sociality

Science.gov (United States)

Willson, Michele

Technologically networked social forms are broad, extensive and in demand. The rapid development and growth of web 2.0, or the social web, is evidence of the need and indeed hunger for social connectivity: people are searching for many and varied ways of enacting being-together. However, the ways in which we think of, research and write about network(ed) sociality are relatively recent and arguably restricted, warranting further critique and development. This article attempts to do several things: it raises questions about the types of sociality enacted in contemporary techno-society; critically explores the notion of the networked individual and the focus on the individual evident in much of the technology and sociality literature and asks questions about the place of the social in these discussions. It argues for a more well-balanced and multilevelled approach to questions of sociality in networked societies. The article starts from the position that possibilities enabled/afforded by the technologies we have in place have an effect upon the ways in which we understand being in the world together and our possible actions and futures. These possibilities are more than simply supplementary; in many ways they are transformative. The ways in which we grapple with these questions reveals as much about our understandings of sociality as it does about the technologies themselves.

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.

From biological and social network metaphors to coupled bio-social wireless networks

Science.gov (United States)

Barrett, Christopher L.; Eubank, Stephen; Anil Kumar, V.S.; Marathe, Madhav V.

2010-01-01

Biological and social analogies have been long applied to complex systems. Inspiration has been drawn from biological solutions to solve problems in engineering products and systems, ranging from Velcro to camouflage to robotics to adaptive and learning computing methods. In this paper, we present an overview of recent advances in understanding biological systems as networks and use this understanding to design and analyse wireless communication networks. We expand on two applications, namely cognitive sensing and control and wireless epidemiology. We discuss how our work in these two applications is motivated by biological metaphors. We believe that recent advances in computing and communications coupled with advances in health and social sciences raise the possibility of studying coupled bio-social communication networks. We argue that we can better utilise the advances in our understanding of one class of networks to better our understanding of the other. PMID:21643462

Associating Human-Centered Concepts with Social Networks Using Fuzzy Sets

Science.gov (United States)

Yager, Ronald R.

The rapidly growing global interconnectivity, brought about to a large extent by the Internet, has dramatically increased the importance and diversity of social networks. Modern social networks cut across a spectrum from benign recreational focused websites such as Facebook to occupationally oriented websites such as LinkedIn to criminally focused groups such as drug cartels to devastation and terror focused groups such as Al-Qaeda. Many organizations are interested in analyzing and extracting information related to these social networks. Among these are governmental police and security agencies as well marketing and sales organizations. To aid these organizations there is a need for technologies to model social networks and intelligently extract information from these models. While established technologies exist for the modeling of relational networks [1-7] few technologies exist to extract information from these, compatible with human perception and understanding. Data bases is an example of a technology in which we have tools for representing our information as well as tools for querying and extracting the information contained. Our goal is in some sense analogous. We want to use the relational network model to represent information, in this case about relationships and interconnections, and then be able to query the social network using intelligent human-centered concepts. To extend our capabilities to interact with social relational networks we need to associate with these network human concepts and ideas. Since human beings predominantly use linguistic terms in which to reason and understand we need to build bridges between human conceptualization and the formal mathematical representation of the social network. Consider for example a concept such as "leader". An analyst may be able to express, in linguistic terms, using a network relevant vocabulary, properties of a leader. Our task is to translate this linguistic description into a mathematical formalism

Fundamental structures of dynamic social networks

DEFF Research Database (Denmark)

Sekara, Vedran; Stopczynski, Arkadiusz; Jørgensen, Sune Lehmann

2016-01-01

Social systems are in a constant state of flux, with dynamics spanning from minute-by-minute changes to patterns present on the timescale of years. Accurate models of social dynamics are important for understanding the spreading of influence or diseases, formation of friendships...... and their interactions in the network of real-world person-to-person proximity measured via Bluetooth, as well as their telecommunication networks, online social media contacts, geolocation, and demographic data. These high-resolution data allow us to observe social groups directly, rendering community detection......, and the productivity of teams. Although there has been much progress on understanding complex networks over the past decade, little is known about the regularities governing the microdynamics of social networks. Here, we explore the dynamic social network of a densely-connected population of ∼1,000 individuals...

A meta-analysis of social networking online and social capital

NARCIS (Netherlands)

Liu, Dong; Ainsworth, Sarah E.; Baumeister, Roy F.

2016-01-01

Social networking sites offer new avenues for interpersonal communication that may enable people to build social capital. The meta-analyses reported in this paper evaluated the relationship between social network site (SNS) use and 2 types of social capital: bridging social capital and bonding

Digital Divides and Social Network Sites: Which Students Participate in Social Media?

Science.gov (United States)

Ahn, June

2011-01-01

Social network sites (SNSs) like Myspace and Facebook are now popular online communities with large teenage user populations. Teens use these technologies to interact, play, explore, and learn in significant ways. As scholars become interested in studying these new online communities, I contribute to the emerging conversation by re-examining…

Use of social network sites and instant messaging does not lead to increased offline social network size, or to emotionally closer relationships with offline network members.

Science.gov (United States)

Pollet, Thomas V; Roberts, Sam G B; Dunbar, Robin I M

2011-04-01

The effect of Internet use on social relationships is still a matter of intense debate. This study examined the relationships between use of social media (instant messaging and social network sites), network size, and emotional closeness in a sample of 117 individuals aged 18 to 63 years old. Time spent using social media was associated with a larger number of online social network "friends." However, time spent using social media was not associated with larger offline networks, or feeling emotionally closer to offline network members. Further, those that used social media, as compared to non-users of social media, did not have larger offline networks, and were not emotionally closer to offline network members. These results highlight the importance of considering potential time and cognitive constraints on offline social networks when examining the impact of social media use on social relationships.

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.

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.

Postdiagnosis social networks and breast cancer mortality in the After Breast Cancer Pooling Project.

Science.gov (United States)

Kroenke, Candyce H; Michael, Yvonne L; Poole, Elizabeth M; Kwan, Marilyn L; Nechuta, Sarah; Leas, Eric; Caan, Bette J; Pierce, John; Shu, Xiao-Ou; Zheng, Ying; Chen, Wendy Y

2017-04-01

Large social networks have been associated with better overall survival, though not consistently with breast cancer (BC)-specific outcomes. This study evaluated associations of postdiagnosis social networks and BC outcomes in a large cohort. Women from the After Breast Cancer Pooling Project (n = 9267) provided data on social networks within approximately 2 years of their diagnosis. A social network index was derived from information about the presence of a spouse/partner, religious ties, community ties, friendship ties, and numbers of living first-degree relatives. Cox models were used to evaluate associations, and a meta-analysis was used to determine whether effect estimates differed by cohort. Stratification by demographic, social, tumor, and treatment factors was performed. There were 1448 recurrences and 1521 deaths (990 due to BC). Associations were similar in 3 of 4 cohorts. After covariate adjustments, socially isolated women (small networks) had higher risks of recurrence (hazard ratio [HR], 1.43; 95% confidence interval [CI], 1.15-1.77), BC-specific mortality (HR, 1.64; 95% CI, 1.33-2.03), and total mortality (HR, 1.69; 95% CI, 1.43-1.99) than socially integrated women; associations were stronger in those with stage I/II cancer. In the fourth cohort, there were no significant associations with BC-specific outcomes. A lack of a spouse/partner (P = .02) and community ties (P = .04) predicted higher BC-specific mortality in older white women but not in other women. However, a lack of relatives (P = .02) and friendship ties (P = .01) predicted higher BC-specific mortality in nonwhite women only. In a large pooled cohort, larger social networks were associated with better BC-specific and overall survival. Clinicians should assess social network information as a marker of prognosis because critical supports may differ with sociodemographic factors. Cancer 2017;123:1228-1237. © 2016 American Cancer Society. © 2016 American Cancer Society.

Agonistic reciprocity is associated with reduced male reproductive success within haremic social networks

Science.gov (United States)

Solomon-Lane, Tessa K.; Pradhan, Devaleena S.; Willis, Madelyne C.; Grober, Matthew S.

2015-01-01

While individual variation in social behaviour is ubiquitous and causes social groups to differ in structure, how these structural differences affect fitness remains largely unknown. We used social network analysis of replicate bluebanded goby (Lythrypnus dalli) harems to identify the reproductive correlates of social network structure. In stable groups, we quantified agonistic behaviour, reproduction and steroid hormones, which can both affect and respond to social/reproductive cues. We identified distinct, optimal social structures associated with different reproductive measures. Male hatching success (HS) was negatively associated with agonistic reciprocity, a network structure that describes whether subordinates ‘reciprocated’ agonism received from dominants. Egg laying was associated with the individual network positions of the male and dominant female. Thus, males face a trade-off between promoting structures that facilitate egg laying versus HS. Whether this reproductive conflict is avoidable remains to be determined. We also identified different social and/or reproductive roles for 11-ketotestosterone, 17β-oestradiol and cortisol, suggesting that specific neuroendocrine mechanisms may underlie connections between network structure and fitness. This is one of the first investigations of the reproductive and neuroendocrine correlates of social behaviour and network structure in replicate, naturalistic social groups and supports network structure as an important target for natural selection. PMID:26156769

Social networks and treatment adherence among Latino offenders with mental illness.

Science.gov (United States)

Eno Louden, Jennifer; Manchak, Sarah M

2018-02-01

Mental health treatment adherence is often required for offenders with mental illness supervised on probation and parole. However, research on offenders with mental illness has largely overlooked cultural and ethnic responsivity factors that may affect adherence to treatment. Latinos are a quickly growing subgroup of offenders whose social networks differ in meaningful ways from European Americans' (e.g., size, composition, centrality of family). Social networks are known to relate to both clinical and criminal justice outcomes for offenders with mental illness, and there are features of nonoffender Latinos' social networks that suggest that findings distilled from work with non-Latino offenders may not apply to them. The present study examined the social networks of 86 Latino probationers with serious mental illness to (a) describe the size and composition of these networks and (b) to determine which factors of social networks are related to treatment adherence. The authors found that Latino offenders' social networks are small (∼6 individuals), consisting primarily of family and professionals such as treatment providers and probation officers. Supportive relationships with nonprofessionals and treatment providers was related to lower likelihood of missing treatment appointments, whereas social control and pressure from family and friends to attend treatment was not related to treatment adherence. Findings are discussed within the context of improved practices for community corrections and mental health agencies in working with Latino offenders with mental illness. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Evolution of individual versus social learning on social networks.

Science.gov (United States)

Tamura, Kohei; Kobayashi, Yutaka; Ihara, Yasuo

2015-03-06

A number of studies have investigated the roles played by individual and social learning in cultural phenomena and the relative advantages of the two learning strategies in variable environments. Because social learning involves the acquisition of behaviours from others, its utility depends on the availability of 'cultural models' exhibiting adaptive behaviours. This indicates that social networks play an essential role in the evolution of learning. However, possible effects of social structure on the evolution of learning have not been fully explored. Here, we develop a mathematical model to explore the evolutionary dynamics of learning strategies on social networks. We first derive the condition under which social learners (SLs) are selectively favoured over individual learners in a broad range of social network. We then obtain an analytical approximation of the long-term average frequency of SLs in homogeneous networks, from which we specify the condition, in terms of three relatedness measures, for social structure to facilitate the long-term evolution of social learning. Finally, we evaluate our approximation by Monte Carlo simulations in complete graphs, regular random graphs and scale-free networks. We formally show that whether social structure favours the evolution of social learning is determined by the relative magnitudes of two effects of social structure: localization in competition, by which competition between learning strategies is evaded, and localization in cultural transmission, which slows down the spread of adaptive traits. In addition, our estimates of the relatedness measures suggest that social structure disfavours the evolution of social learning when selection is weak. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Social Networks and Technology Adoption

OpenAIRE

Hogset, Heidi

2005-01-01

This study analyzes social network effects on Kenyan smallholders' decision to adopt improved natural resource management techniques. These effects are decomposed into effects from social influence and learning through networks (strong ties), group effects, weak ties effects, informal finance, and conflicts arising from technological externalities, controlling for non-network effects.

Multilevel compression of random walks on networks reveals hierarchical organization in large integrated systems.

Directory of Open Access Journals (Sweden)

Martin Rosvall

Full Text Available To comprehend the hierarchical organization of large integrated systems, we introduce the hierarchical map equation, which reveals multilevel structures in networks. In this information-theoretic approach, we exploit the duality between compression and pattern detection; by compressing a description of a random walker as a proxy for real flow on a network, we find regularities in the network that induce this system-wide flow. Finding the shortest multilevel description of the random walker therefore gives us the best hierarchical clustering of the network--the optimal number of levels and modular partition at each level--with respect to the dynamics on the network. With a novel search algorithm, we extract and illustrate the rich multilevel organization of several large social and biological networks. For example, from the global air traffic network we uncover countries and continents, and from the pattern of scientific communication we reveal more than 100 scientific fields organized in four major disciplines: life sciences, physical sciences, ecology and earth sciences, and social sciences. In general, we find shallow hierarchical structures in globally interconnected systems, such as neural networks, and rich multilevel organizations in systems with highly separated regions, such as road networks.

Social networks, social support and psychiatric symptoms: social determinants and associations within a multicultural community population.

Science.gov (United States)

Smyth, Natasha; Siriwardhana, Chesmal; Hotopf, Matthew; Hatch, Stephani L

2015-07-01

Little is known about how social networks and social support are distributed within diverse communities and how different types of each are associated with a range of psychiatric symptoms. This study aims to address such shortcomings by: (1) describing the demographic and socioeconomic characteristics of social networks and social support in a multicultural population and (2) examining how each is associated with multiple mental health outcomes. Data is drawn from the South East London Community Health Study; a cross-sectional study of 1,698 adults conducted between 2008 and 2010. The findings demonstrate variation in social networks and social support by socio-demographic factors. Ethnic minority groups reported larger family networks but less perceived instrumental support. Older individuals and migrant groups reported lower levels of particular network and support types. Individuals from lower socioeconomic groups tended to report less social networks and support across the indicators measured. Perceived emotional and instrumental support, family and friend network size emerged as protective factors for common mental disorder, personality dysfunction and psychotic experiences. In contrast, both social networks and social support appear less relevant for hazardous alcohol use. The findings both confirm established knowledge that social networks and social support exert differential effects on mental health and furthermore suggest that the particular type of social support may be important. In contrast, different types of social network appear to impact upon poor mental health in a more uniform way. Future psychosocial strategies promoting mental health should consider which social groups are vulnerable to reduced social networks and poor social support and which diagnostic groups may benefit most.

Understanding Social Networks: Theories, Concepts, and Findings

Science.gov (United States)

Kadushin, Charles

2012-01-01

Despite the swift spread of social network concepts and their applications and the rising use of network analysis in social science, there is no book that provides a thorough general introduction for the serious reader. "Understanding Social Networks" fills that gap by explaining the big ideas that underlie the social network phenomenon.…

The network researchers' network: A social network analysis of the IMP Group 1985-2006

DEFF Research Database (Denmark)

Henneberg, Stephan C. M.; Ziang, Zhizhong; Naudé, Peter

The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987......). In this paper, based upon the papers presented at the 22 conferences held to date, we undertake a Social Network Analysis in order to examine the degree of co-publishing that has taken place between this group of researchers. We identify the different components in this database, and examine the large main...

Networking for philanthropy: increasing volunteer behavior via social networking sites.

Science.gov (United States)

Kim, Yoojung; Lee, Wei-Na

2014-03-01

Social networking sites (SNSs) provide a unique social venue to engage the young generation in philanthropy through their networking capabilities. An integrated model that incorporates social capital into the Theory of Reasoned Action is developed to explain volunteer behavior through social networks. As expected, volunteer behavior was predicted by volunteer intention, which was influenced by attitudes and subjective norms. In addition, social capital, an outcome of the extensive use of SNSs, was as an important driver of users' attitude and subjective norms toward volunteering via SNSs.

Can mental health interventions change social networks? A systematic review.

Science.gov (United States)

Anderson, Kimberley; Laxhman, Neelam; Priebe, Stefan

2015-11-21

Social networks of patients with psychosis can provide social support, and improve health and social outcomes, including quality of life. However, patients with psychosis often live rather isolated with very limited social networks. Evidence for interventions targeting symptoms or social skills, are largely unsuccessful at improving social networks indirectly. As an alternative, interventions may directly focus on expanding networks. In this systematic review, we assessed what interventions have previously been tested for this and to what extent they have been effective. A systematic review was conducted of randomised controlled trials, testing psychosocial interventions designed to directly increase the social networks of patients with psychosis. Searches of five online databases (PsycINFO, CINAHL, Cochrane Database, MEDLINE, Embase), hand searching of grey literature, and both forward and backward snowballing of key papers were conducted and completed on 12 December 2014. Trial reports were included if they were written in English, the social network size was the primary outcome, participants were ≥ 18 years old and diagnosed with a psychotic disorder. Five studies (n = 631 patients) met the complete inclusion criteria. Studies were from different countries and published since 2008. Four trials had significant positive results, i.e. an observable increase in patients' social network size at the end of the intervention. The interventions included: guided peer support, a volunteer partner scheme, supported engagement in social activity, dog-assisted integrative psychological therapy and psychosocial skills training. Other important elements featured were the presence of a professional, and a focus on friendships and peers outside of services and the immediate family. Despite the small number and heterogeneity of included studies, the results suggest that interventions directly targeting social isolation can be effective and achieve a meaningful increase

Analyzing negative ties in social networks

Directory of Open Access Journals (Sweden)

Mankirat Kaur

2016-03-01

Full Text Available Online social networks are a source of sharing information and maintaining personal contacts with other people through social interactions and thus forming virtual communities online. Social networks are crowded with positive and negative relations. Positive relations are formed by support, endorsement and friendship and thus, create a network of well-connected users whereas negative relations are a result of opposition, distrust and avoidance creating disconnected networks. Due to increase in illegal activities such as masquerading, conspiring and creating fake profiles on online social networks, exploring and analyzing these negative activities becomes the need of hour. Usually negative ties are treated in same way as positive ties in many theories such as balance theory and blockmodeling analysis. But the standard concepts of social network analysis do not yield same results in respect of each tie. This paper presents a survey on analyzing negative ties in social networks through various types of network analysis techniques that are used for examining ties such as status, centrality and power measures. Due to the difference in characteristics of flow in positive and negative tie networks some of these measures are not applicable on negative ties. This paper also discusses new methods that have been developed specifically for analyzing negative ties such as negative degree, and h∗ measure along with the measures based on mixture of positive and negative ties. The different types of social network analysis approaches have been reviewed and compared to determine the best approach that can appropriately identify the negative ties in online networks. It has been analyzed that only few measures such as Degree and PN centrality are applicable for identifying outsiders in network. For applicability in online networks, the performance of PN measure needs to be verified and further, new measures should be developed based upon negative clique concept.

Underage Children and Social Networking

Science.gov (United States)

Weeden, Shalynn; Cooke, Bethany; McVey, Michael

2013-01-01

Despite minimum age requirements for joining popular social networking services such as Facebook, many students misrepresent their real ages and join as active participants in the networks. This descriptive study examines the use of social networking services (SNSs) by children under the age of 13. The researchers surveyed a sample of 199…

The ART of social networking: how SART member clinics are connecting with patients online.

Science.gov (United States)

Omurtag, Kenan; Jimenez, Patricia T; Ratts, Valerie; Odem, Randall; Cooper, Amber R

2012-01-01

To study and describe the use of social networking websites among Society for Assisted Reproductive Technology (SART) member clinics. Cross-sectional study. University-based practice. Not applicable. Not applicable. Prevalence of social networking websites among SART member clinics and evaluation of content, volume, and location (i.e., mandated state, region) using multivariate regression analysis. A total of 384 SART-registered clinics and 1,382 social networking posts were evaluated. Of the clinics, 96% had a website and 30% linked to a social networking website. The majority of clinics (89%) with social networking websites were affiliated with nonacademic centers. Social networking posts mostly provided information (31%) and/or advertising (28%), and the remaining offered support (19%) or were irrelevant (17%) to the target audience. Only 5% of posts involved patients requesting information. Clinic volume correlated with the presence of a clinic website and a social networking website. Almost all SART member clinics have a website. Nearly one-third of these clinics host a social networking website such as Facebook, Twitter, and/or a blog. Large-volume clinics commonly host social networking websites. These sites provide new ways to communicate with patients, but clinics should maintain policies on the incorporation of social networks into practice. Copyright © 2012 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Networking, or What the Social Means in Social Media

OpenAIRE

Taina Bucher

2015-01-01

This article questions the meaning of the social in social media. It does this by revisiting boyd and Ellison’s seminal paper and definition of social network sites. The article argues that social media are not so much about articulating or making an existing network visible. Rather, being social in the context of social media simply means creating connections within the boundaries of adaptive algorithmic architectures. Every click, share, like, and post creates a connection, initiates a rela...

Brand Marketing Model on Social Networks

OpenAIRE

Jolita Jezukevičiūtė; Vida Davidavičienė

2014-01-01

The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalys...

Data mining for social network data

CERN Document Server

Memon, Nasrullah; Hicks, David L; Chen, Hsinchun

2010-01-01

Driven by counter-terrorism efforts, marketing analysis and an explosion in online social networking in recent years, data mining has moved to the forefront of information science. This proposed Special Issue on ""Data Mining for Social Network Data"" will present a broad range of recent studies in social networking analysis. It will focus on emerging trends and needs in discovery and analysis of communities, solitary and social activities, and activities in open fora, and commercial sites as well. It will also look at network modeling, infrastructure construction, dynamic growth and evolution

A New Graph Drawing Scheme for Social Network

Directory of Open Access Journals (Sweden)

Eric Ke Wang

2014-01-01

visualization is employed to extract the potential information from the large scale of social network data and present the information briefly as visualized graphs. In the process of information visualization, graph drawing is a crucial part. In this paper, we study the graph layout algorithms and propose a new graph drawing scheme combining multilevel and single-level drawing approaches, including the graph division method based on communities and refining approach based on partitioning strategy. Besides, we compare the effectiveness of our scheme and FM3 in experiments. The experiment results show that our scheme can achieve a clearer diagram and effectively extract the community structure of the social network to be applied to drawing schemes.

A multilevel path analysis of contact frequency between social network members

Science.gov (United States)

van den Berg, Pauline; Arentze, Theo; Timmermans, Harry

2012-04-01

Recently, there has been an increasing interest in the role of social networks in spatial-choice and travel behavior. It has been acknowledged that social activities and the travel for these activities can emerge from individuals' social networks and that social activities are responsible for an important portion of travel demand. The influence of information and communication technologies (ICT's) is also important in this respect. The purpose of the paper is to examine the effects of characteristics of egos and ego-alter relationships on the frequency of social interaction by different communication modes, using multilevel path analysis. The analyses are based on social network data collected in 2008 in the Eindhoven region in the Netherlands among 116 respondents. The results indicate a complementary relationship between contact frequencies by different modes. The contact frequencies of the different modes, especially face-to-face and telephone, can also be largely explained by the ego's personal characteristics and the type of relationship and the distance between ego and alter.

Philosophy of social networking

Directory of Open Access Journals (Sweden)

Markova T. V.

2018-04-01

Full Text Available the article is devoted to the study of social networks impact on an individual, which are an important part of a modern society. Through reflections the reasons of the popularity of the phenomenon of virtual communication in the 21st century are determined: what drives a person when he / she registers on the sites for communication, premises for his / her actions and consequences. The latter is viewed from both a social and a personal point of view. After analyzing the charts of social networks popularity, the authors come to the conclusion that there is an increase in the population of the virtual communication supporters. It allows to assert that the problem of the termination of live communication is relevant to this day. Dualism of social networks influence on the consciousness of an individual is stated: together with negative consequences positive aspects are considered. By analyzing social media researches, as well as by the means of a survey, the dominant reason for the world wide web entering is identified. After that, it is clearly shown what a typical site for communication is; as a result, the pros and cons of such time spending are specified. The conclusion states the predominance of the Internet dependence over the other types of dependencies, also forecasts are made for the future of both social networks and the people caught in their web.

Volunteerism: Social Network Dynamics and Education

Science.gov (United States)

Ajrouch, Kristine J.; Antonucci, Toni C.; Webster, Noah J.

2016-01-01

Objectives . We examine how changes in social networks influence volunteerism through bridging (diversity) and bonding (spending time) mechanisms. We further investigate whether social network change substitutes or amplifies the effects of education on volunteerism. Methods . Data (n = 543) are drawn from a two-wave survey of Social Relations and Health over the Life Course (SRHLC). Zero-inflated negative binomial regressions were conducted to test competing hypotheses about how changes in social network characteristics alone and in conjunction with education level predict likelihood and frequency of volunteering. Results . Changes in social networks were associated with volunteerism: as the proportion of family members decreased and the average number of network members living within a one-hour drive increased over time, participants reported higher odds of volunteering. The substitution hypothesis was supported: social networks that exhibited more geographic proximity and greater contact frequency over-time compensated for lower levels of education to predict volunteering more hours. Discussion . The dynamic role of social networks and the ways in which they may work through bridging and bonding to influence both likelihood and frequency of volunteering are discussed. The potential benefits of volunteerism in light of longer life expectancies and smaller families are also considered. PMID:25512570

Modeling cascading failures with the crisis of trust in social networks

Science.gov (United States)

Yi, Chengqi; Bao, Yuanyuan; Jiang, Jingchi; Xue, Yibo

2015-10-01

In social networks, some friends often post or disseminate malicious information, such as advertising messages, informal overseas purchasing messages, illegal messages, or rumors. Too much malicious information may cause a feeling of intense annoyance. When the feeling exceeds a certain threshold, it will lead social network users to distrust these friends, which we call the crisis of trust. The crisis of trust in social networks has already become a universal concern and an urgent unsolved problem. As a result of the crisis of trust, users will cut off their relationships with some of their untrustworthy friends. Once a few of these relationships are made unavailable, it is likely that other friends will decline trust, and a large portion of the social network will be influenced. The phenomenon in which the unavailability of a few relationships will trigger the failure of successive relationships is known as cascading failure dynamics. To our best knowledge, no one has formally proposed cascading failures dynamics with the crisis of trust in social networks. In this paper, we address this potential issue, quantify the trust between two users based on user similarity, and model the minimum tolerance with a nonlinear equation. Furthermore, we construct the processes of cascading failures dynamics by considering the unique features of social networks. Based on real social network datasets (Sina Weibo, Facebook and Twitter), we adopt two attack strategies (the highest trust attack (HT) and the lowest trust attack (LT)) to evaluate the proposed dynamics and to further analyze the changes of the topology, connectivity, cascading time and cascade effect under the above attacks. We numerically find that the sparse and inhomogeneous network structure in our cascading model can better improve the robustness of social networks than the dense and homogeneous structure. However, the network structure that seems like ripples is more vulnerable than the other two network

Conditions for Viral Influence Spreading through Multiplex Correlated Social Networks

Science.gov (United States)

Hu, Yanqing; Havlin, Shlomo; Makse, Hernán A.

2014-04-01

A fundamental problem in network science is to predict how certain individuals are able to initiate new networks to spring up "new ideas." Frequently, these changes in trends are triggered by a few innovators who rapidly impose their ideas through "viral" influence spreading, producing cascades of followers and fragmenting an old network to create a new one. Typical examples include the rise of scientific ideas or abrupt changes in social media, like the rise of Facebook to the detriment of Myspace. How this process arises in practice has not been conclusively demonstrated. Here, we show that a condition for sustaining a viral spreading process is the existence of a multiplex-correlated graph with hidden "influence links." Analytical solutions predict percolation-phase transitions, either abrupt or continuous, where networks are disintegrated through viral cascades of followers, as in empirical data. Our modeling predicts the strict conditions to sustain a large viral spreading via a scaling form of the local correlation function between multilayers, which we also confirm empirically. Ultimately, the theory predicts the conditions for viral cascading in a large class of multiplex networks ranging from social to financial systems and markets.

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...

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%.

Modeling Social Capital as Dynamic Networks to Promote Access to Oral Healthcare.

Science.gov (United States)

Wang, Hua; Northridge, Mary E; Kunzel, Carol; Zhang, Qiuyi; Kum, Susan S; Gilbert, Jessica L; Jin, Zhu; Metcalf, Sara S

2016-01-01

Social capital, as comprised of human connections in social networks and their associated benefits, is closely related to the health of individuals, communities, and societies at large. For disadvantaged population groups such as older adults and racial/ethnic minorities, social capital may play a particularly critical role in mitigating the negative effects and reinforcing the positive effects on health. In this project, we model social capital as both cause and effect by simulating dynamic networks. Informed in part by a community-based health promotion program, an agent-based model is contextualized in a GIS environment to explore the complexity of social disparities in oral and general health as experienced at the individual, interpersonal, and community scales. This study provides the foundation for future work investigating how health and healthcare accessibility may be influenced by social networks.

Information Dissemination of Public Health Emergency on Social Networks and Intelligent Computation

Directory of Open Access Journals (Sweden)

Hongzhi Hu

2015-01-01

Full Text Available Due to the extensive social influence, public health emergency has attracted great attention in today’s society. The booming social network is becoming a main information dissemination platform of those events and caused high concerns in emergency management, among which a good prediction of information dissemination in social networks is necessary for estimating the event’s social impacts and making a proper strategy. However, information dissemination is largely affected by complex interactive activities and group behaviors in social network; the existing methods and models are limited to achieve a satisfactory prediction result due to the open changeable social connections and uncertain information processing behaviors. ACP (artificial societies, computational experiments, and parallel execution provides an effective way to simulate the real situation. In order to obtain better information dissemination prediction in social networks, this paper proposes an intelligent computation method under the framework of TDF (Theory-Data-Feedback based on ACP simulation system which was successfully applied to the analysis of A (H1N1 Flu emergency.

The model of social crypto-network

Directory of Open Access Journals (Sweden)

Марк Миколайович Орел

2015-06-01

Full Text Available The article presents the theoretical model of social network with the enhanced mechanism of privacy policy. It covers the problems arising in the process of implementing the mentioned type of network. There are presented the methods of solving problems arising in the process of building the social network with privacy policy. It was built a theoretical model of social networks with enhanced information protection methods based on information and communication blocks

Animal welfare: a social networks perspective.

Science.gov (United States)

Kleinhappel, Tanja K; John, Elizabeth A; Pike, Thomas W; Wilkinson, Anna; Burman, Oliver H P

2016-01-01

Social network theory provides a useful tool to study complex social relationships in animals. The possibility to look beyond dyadic interactions by considering whole networks of social relationships allows researchers the opportunity to study social groups in more natural ways. As such, network-based analyses provide an informative way to investigate the factors influencing the social environment of group-living animals, and so has direct application to animal welfare. For example, animal groups in captivity are frequently disrupted by separations, reintroductions and/or mixing with unfamiliar individuals and this can lead to social stress and associated aggression. Social network analysis ofanimal groups can help identify the underlying causes of these socially-derived animal welfare concerns. In this review we discuss how this approach can be applied, and how it could be used to identify potential interventions and solutions in the area of animal welfare.

Social Networks and Social Revolution. Evidence from Romania

Directory of Open Access Journals (Sweden)

Androniciuc Andra

2017-01-01

No other means of communication have had such a rapid development as the Internet, a mediumthat is undoubtedly changing the rules of the political game. In this article, we take a look at theuse of social networks during social and political movements, with particular focus on the 2014,2015 and 2017 Romanian protests. We conclude that social networks alone do not instigaterevolutions, but they are valuable tools for citizens to organize free protests, recruit and trainparticipants, which can lead to further collective action and social change.

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.

Connecting Mobile Users Through Mobile Social Networks

Directory of Open Access Journals (Sweden)

Faisal Alkhateeb

2012-10-01

Full Text Available Nowadays, social networks become popular with the emerging of web-based social networking services. Recently, several mobile services are developed to connect users to their favourite social networks such as Facebook, Twitter, Flickr, etc. However, these services depends upon the existing web-based social networks. In this paper, we present a mobile service for joining groups across communities. The originality of the work is that the framework of the service allows creating and joining social networks that are self-contained for mobile company servers. The service consists of several sub-services such as users invitation, group finding and others. Users, regardless of their disability, can use the service and its sub-services without the need to create their own accounts on social web sites and thus their own groups. We also propose a privacy control policy for mobile social networks.

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

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

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.

Influencing Busy People in a Social Network.

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Sarkar, Kaushik; Sundaram, Hari

2016-01-01

We identify influential early adopters in a social network, where individuals are resource constrained, to maximize the spread of multiple, costly behaviors. A solution to this problem is especially important for viral marketing. The problem of maximizing influence in a social network is challenging since it is computationally intractable. We make three contributions. First, we propose a new model of collective behavior that incorporates individual intent, knowledge of neighbors actions and resource constraints. Second, we show that the multiple behavior influence maximization is NP-hard. Furthermore, we show that the problem is submodular, implying the existence of a greedy solution that approximates the optimal solution to within a constant. However, since the greedy algorithm is expensive for large networks, we propose efficient heuristics to identify the influential individuals, including heuristics to assign behaviors to the different early adopters. We test our approach on synthetic and real-world topologies with excellent results. We evaluate the effectiveness under three metrics: unique number of participants, total number of active behaviors and network resource utilization. Our heuristics produce 15-51% increase in expected resource utilization over the naïve approach.

Influencing Busy People in a Social Network

Science.gov (United States)

Sarkar, Kaushik; Sundaram, Hari

2016-01-01

We identify influential early adopters in a social network, where individuals are resource constrained, to maximize the spread of multiple, costly behaviors. A solution to this problem is especially important for viral marketing. The problem of maximizing influence in a social network is challenging since it is computationally intractable. We make three contributions. First, we propose a new model of collective behavior that incorporates individual intent, knowledge of neighbors actions and resource constraints. Second, we show that the multiple behavior influence maximization is NP-hard. Furthermore, we show that the problem is submodular, implying the existence of a greedy solution that approximates the optimal solution to within a constant. However, since the greedy algorithm is expensive for large networks, we propose efficient heuristics to identify the influential individuals, including heuristics to assign behaviors to the different early adopters. We test our approach on synthetic and real-world topologies with excellent results. We evaluate the effectiveness under three metrics: unique number of participants, total number of active behaviors and network resource utilization. Our heuristics produce 15-51% increase in expected resource utilization over the naïve approach. PMID:27711127

Social networks and employment in India

OpenAIRE

Tushar K. Nandi

2010-01-01

We investigate the influence of social networks on employment. Using data from India, we estimate the effect of caste based social networks on employment. We use a methodology that allows us to control for several omitted variable biases that often confound network effect. Our results indicate that caste based social networks are important determinant of employment in India. The implication of our findings is that a policy of positive discrimination in labour market for disadvantaged caste is...

Information filtering on coupled social networks.

Science.gov (United States)

Nie, Da-Cheng; Zhang, Zi-Ke; Zhou, Jun-Lin; Fu, Yan; Zhang, Kui

2014-01-01

In this paper, based on the coupled social networks (CSN), we propose a hybrid algorithm to nonlinearly integrate both social and behavior information of online users. Filtering algorithm, based on the coupled social networks, considers the effects of both social similarity and personalized preference. Experimental results based on two real datasets, Epinions and Friendfeed, show that the hybrid pattern can not only provide more accurate recommendations, but also enlarge the recommendation coverage while adopting global metric. Further empirical analyses demonstrate that the mutual reinforcement and rich-club phenomenon can also be found in coupled social networks where the identical individuals occupy the core position of the online system. This work may shed some light on the in-depth understanding of the structure and function of coupled social networks.

Handbook of social network technologies and applications

CERN Document Server

Furht, Borko

2010-01-01

Social networking is a concept that has existed for a long time; however, with the explosion of the Internet, social networking has become a tool for people to connect and communicate in ways that were impossible in the past. The recent development of Web 2.0 has provided many new applications, such as Myspace, Facebook, and LinkedIn. The purpose of ""Handbook of Social Networks: Technologies and Applications"" is to provide comprehensive guidelines on the current and future trends in social network technologies and applications in the field of Web-based Social Networks. This handbook includes

Subjective social status, social network and health disparities: empirical evidence from Greece.

Science.gov (United States)

Charonis, Antonios; Kyriopoulos, Ilias-Ioannis; Spanakis, Manos; Zavras, Dimitris; Athanasakis, Kostas; Pavi, Elpida; Kyriopoulos, John

2017-02-27

Several studies suggest that socioeconomic status affects (SES) affects self-rated health (SRH), both in Greece and internationally. However, prior research mainly uses objective measures of SES, instead of subjective evaluations of individuals' social status. Based on this, this paper aims to examine (a) the impact of the economic dowturn on SRH in Greece and (b) the relationship between subjective social status (SSS), social network and SRH. The descriptive analysis is based on four cross-sectional surveys conducted by the National School of Public Health, Athens, Greece (2002, 2006, 2011, 2015), while the data for the empirical investigation were derived from the 2015 survey (Health + Welfare Survey GR). The empirical strategy is based on an ordinal logistic regression model, aiming to examine how several variables affect SRH. Size of social network and SSS are among the independent variables employed for the empirical analysis RESULTS: According to our findings, average SRH has deteriorated, and the percentage of the population that reports very good/good SRH has also decreased. Moreover, our empirical analysis suggests that age, existence of a chronic disease, size of social network and SSS affect SRH in Greece. Our findings are consistent with the existing literature and confirm a social gradient in health. According to our analysis, health disparities can be largely attributed to socioeconomic inequalities. The adverse economic climate has impact on socioeconomic differences which in turn affect health disparities. Based on these, policy initiatives are necessasy in order to mitigate the negative impact on health and the disparities caused by economic dowturn and the occuring socioeconomic inequalities.

The Analysis of Duocentric Social Networks: A Primer.

Science.gov (United States)

Kennedy, David P; Jackson, Grace L; Green, Harold D; Bradbury, Thomas N; Karney, Benjamin R

2015-02-01

Marriages and other intimate partnerships are facilitated or constrained by the social networks within which they are embedded. To date, methods used to assess the social networks of couples have been limited to global ratings of social network characteristics or network data collected from each partner separately. In the current article, the authors offer new tools for expanding on the existing literature by describing methods of collecting and analyzing duocentric social networks, that is, the combined social networks of couples. They provide an overview of the key considerations for measuring duocentric networks, such as how and why to combine separate network interviews with partners into one shared duocentric network, the number of network members to assess, and the implications of different network operationalizations. They illustrate these considerations with analyses of social network data collected from 57 low-income married couples, presenting visualizations and quantitative measures of network composition and structure.

Networks in social policy problems

CERN Document Server

Scotti, marco

2012-01-01

Network science is the key to managing social communities, designing the structure of efficient organizations and planning for sustainable development. This book applies network science to contemporary social policy problems. In the first part, tools of diffusion and team design are deployed to challenges in adoption of ideas and the management of creativity. Ideas, unlike information, are generated and adopted in networks of personal ties. Chapters in the second part tackle problems of power and malfeasance in political and business organizations, where mechanisms in accessing and controlling informal networks often outweigh formal processes. The third part uses ideas from biology and physics to understand global economic and financial crises, ecological depletion and challenges to energy security. Ideal for researchers and policy makers involved in social network analysis, business strategy and economic policy, it deals with issues ranging from what makes public advisories effective to how networks influenc...

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.

Egocentric Social Network Analysis of Pathological Gambling

Science.gov (United States)

Meisel, Matthew K.; Clifton, Allan D.; MacKillop, James; Miller, Joshua D.; Campbell, W. Keith; Goodie, Adam S.

2012-01-01

Aims To apply social network analysis (SNA) to investigate whether frequency and severity of gambling problems were associated with different network characteristics among friends, family, and co-workers. is an innovative way to look at relationships among individuals; the current study was the first to our knowledge to apply SNA to gambling behaviors. Design Egocentric social network analysis was used to formally characterize the relationships between social network characteristics and gambling pathology. Setting Laboratory-based questionnaire and interview administration. Participants Forty frequent gamblers (22 non-pathological gamblers, 18 pathological gamblers) were recruited from the community. Findings The SNA revealed significant social network compositional differences between the two groups: pathological gamblers (PGs) had more gamblers, smokers, and drinkers in their social networks than did nonpathological gamblers (NPGs). PGs had more individuals in their network with whom they personally gambled, smoked, and drank with than those with who were NPG. Network ties were closer to individuals in their networks who gambled, smoked, and drank more frequently. Associations between gambling severity and structural network characteristics were not significant. Conclusions Pathological gambling is associated with compositional but not structural differences in social networks. Pathological gamblers differ from non-pathological gamblers in the number of gamblers, smokers, and drinkers in their social networks. Homophily within the networks also indicates that gamblers tend to be closer with other gamblers. This homophily may serve to reinforce addictive behaviors, and may suggest avenues for future study or intervention. PMID:23072641

Egocentric social network analysis of pathological gambling.

Science.gov (United States)

Meisel, Matthew K; Clifton, Allan D; Mackillop, James; Miller, Joshua D; Campbell, W Keith; Goodie, Adam S

2013-03-01

To apply social network analysis (SNA) to investigate whether frequency and severity of gambling problems were associated with different network characteristics among friends, family and co-workers is an innovative way to look at relationships among individuals; the current study was the first, to our knowledge, to apply SNA to gambling behaviors. Egocentric social network analysis was used to characterize formally the relationships between social network characteristics and gambling pathology. Laboratory-based questionnaire and interview administration. Forty frequent gamblers (22 non-pathological gamblers, 18 pathological gamblers) were recruited from the community. The SNA revealed significant social network compositional differences between the two groups: pathological gamblers (PGs) had more gamblers, smokers and drinkers in their social networks than did non-pathological gamblers (NPGs). PGs had more individuals in their network with whom they personally gambled, smoked and drank than those with who were NPG. Network ties were closer to individuals in their networks who gambled, smoked and drank more frequently. Associations between gambling severity and structural network characteristics were not significant. Pathological gambling is associated with compositional but not structural differences in social networks. Pathological gamblers differ from non-pathological gamblers in the number of gamblers, smokers and drinkers in their social networks. Homophily within the networks also indicates that gamblers tend to be closer with other gamblers. This homophily may serve to reinforce addictive behaviors, and may suggest avenues for future study or intervention. © 2012 The Authors, Addiction © 2012 Society for the Study of Addiction.

Mobile Social Network in a Cultural Context

DEFF Research Database (Denmark)

Liu, Jun

2010-01-01

, and mobile phone rumours, this study observes that mobile social networks are a way that Chinese people cultivate, maintain and strengthen their guanxi networks. Embedding the reliability of guanxi, the message spreading via mobile communication always enjoys high credibility, while mutual obligation...... of mobile social network in China therefore emanate not only from Information and Communication Technologies, but also from the socio-cultural source - guanxi - deeply rooted in Chinese society.......the chapter “Mobile Social Network in a Cultural Context” examines the guanxi-embedded mobile social network in China. By focusing on three concrete case studies with 56 in-depth interviews, including New Year text message greetings, mobile social networks for job allocations among migrant workers...

Dynamic social networks based on movement

Science.gov (United States)

Scharf, Henry; Hooten, Mevin B.; Fosdick, Bailey K.; Johnson, Devin S.; London, Joshua M.; Durban, John W.

2016-01-01

Network modeling techniques provide a means for quantifying social structure in populations of individuals. Data used to define social connectivity are often expensive to collect and based on case-specific, ad hoc criteria. Moreover, in applications involving animal social networks, collection of these data is often opportunistic and can be invasive. Frequently, the social network of interest for a given population is closely related to the way individuals move. Thus, telemetry data, which are minimally invasive and relatively inexpensive to collect, present an alternative source of information. We develop a framework for using telemetry data to infer social relationships among animals. To achieve this, we propose a Bayesian hierarchical model with an underlying dynamic social network controlling movement of individuals via two mechanisms: an attractive effect and an aligning effect. We demonstrate the model and its ability to accurately identify complex social behavior in simulation, and apply our model to telemetry data arising from killer whales. Using auxiliary information about the study population, we investigate model validity and find the inferred dynamic social network is consistent with killer whale ecology and expert knowledge.

Dissemination Patterns and Associated Network Effects of Sentiments in Social Networks

DEFF Research Database (Denmark)

Hillmann, Robert; Trier, Matthias

2012-01-01

. The dissemination patterns analyzed in this study consist of network motifs based on triples of actors and the ties among them. These motifs are associated with common social network effects to derive meaningful insights about dissemination activities. The data basis includes several thousand social networks...... with textual messages classified according to embedded positive and negative sentiments. Based on this data, sub-networks are extracted and analyzed with a dynamic network motif analysis to determine dissemination patterns and associated network effects. Results indicate that the emergence of digital social...... networks exhibits a strong tendency towards reciprocity, followed by the dominance of hierarchy as an intermediate step leading to social clustering with hubs and transitivity effects for both positive and negative sentiments to the same extend. Sentiments embedded in exchanged textual messages do only...

Applications of social media and social network analysis

CERN Document Server

Kazienko, Przemyslaw

2015-01-01

This collection of contributed chapters demonstrates a wide range of applications within two overlapping research domains: social media analysis and social network analysis. Various methodologies were utilized in the twelve individual chapters including static, dynamic and real-time approaches to graph, textual and multimedia data analysis. The topics apply to reputation computation, emotion detection, topic evolution, rumor propagation, evaluation of textual opinions, friend ranking, analysis of public transportation networks, diffusion in dynamic networks, analysis of contributors to commun

Investigation of Spatial Data with Open Source Social Network Analysis and Geographic Information Systems Applications

Science.gov (United States)

Sabah, L.; Şimşek, M.

2017-11-01

Social networks are the real social experience of individuals in the online environment. In this environment, people use symbolic gestures and mimics, sharing thoughts and content. Social network analysis is the visualization of complex and large quantities of data to ensure that the overall picture appears. It is the understanding, development, quantitative and qualitative analysis of the relations in the social networks of Graph theory. Social networks are expressed in the form of nodes and edges. Nodes are people/organizations, and edges are relationships between nodes. Relations are directional, non-directional, weighted, and weightless. The purpose of this study is to examine the effects of social networks on the evaluation of person data with spatial coordinates. For this, the cluster size and the effect on the geographical area of the circle where the placements of the individual are influenced by the frequently used placeholder feature in the social networks have been studied.

Energy model for rumor propagation on social networks

Science.gov (United States)

Han, Shuo; Zhuang, Fuzhen; He, Qing; Shi, Zhongzhi; Ao, Xiang

2014-01-01

With the development of social networks, the impact of rumor propagation on human lives is more and more significant. Due to the change of propagation mode, traditional rumor propagation models designed for word-of-mouth process may not be suitable for describing the rumor spreading on social networks. To overcome this shortcoming, we carefully analyze the mechanisms of rumor propagation and the topological properties of large-scale social networks, then propose a novel model based on the physical theory. In this model, heat energy calculation formula and Metropolis rule are introduced to formalize this problem and the amount of heat energy is used to measure a rumor’s impact on a network. Finally, we conduct track experiments to show the evolution of rumor propagation, make comparison experiments to contrast the proposed model with the traditional models, and perform simulation experiments to study the dynamics of rumor spreading. The experiments show that (1) the rumor propagation simulated by our model goes through three stages: rapid growth, fluctuant persistence and slow decline; (2) individuals could spread a rumor repeatedly, which leads to the rumor’s resurgence; (3) rumor propagation is greatly influenced by a rumor’s attraction, the initial rumormonger and the sending probability.

Social network correlates of HIV risk-related behaviors among male migrants in China

Directory of Open Access Journals (Sweden)

Wenqing Wang

2017-05-01

Full Text Available Abstract Background Significant domestic and global research has focused on HIV risk among China’s large internal migrant population. Much of this work takes an individual behavior approach while ignoring the critical role social networks play in shaping HIV risk. Methods Based on past studies among migrant men in China of yingchou activities (activities that build and reinforce social networks such as eating, drinking alcohol and patronizing commercial sex, we constructed ego-centric networks for a sample of 385 male migrants recruited from multiple worksites in Beijing. We used a nested-model approach to examine the contribution of social network characteristics to HIV risk at both the variable and model levels. Results As compared to an individual-level model, addition of social network variables significantly improved the fit of the models. Commercial sex norms and condom use norms of core yingchou networks were significantly associated with egos’ commercial sex and condom use respectively. The size of yingchou network was associated with egos’ commercial sex. The network models became more sensitive after network norm measures took into account the intimacy of network ties and allowed for egos’ uncertainty when reporting their alters’ sexual behaviors. Conclusion Results suggest the importance of social network factors and core network members in HIV transmission and risk-reduction interventions for male migrants. Future studies could explore other important social networks among male migrants, consider the intimacy of network ties and egos’ uncertainty about alters’ situations in constructing network norms, and refine the measurement of network size and density.

[Social Networks of Children with Mentally Ill Parents].

Science.gov (United States)

Stiawa, Maja; Kilian, Reinhold

2017-10-01

Social Networks of Children with Mentally Ill Parents Mental illness of parents can be a load situation for children. Supporting social relations might be an important source in such a situation. Social relations can be shown by social network analysis. Studies about social networks and mental health indicate differences regarding structure and potential for support when compared with social networks of healthy individuals. If and how mental illness of parents has an impact on their children's network is widely unknown. This systematic review shows methods and results of studies about social networks of children with mentally ill parents. By systematic search in electronic databases as well as manual search, two studies were found who met the target criteria. Both studies were conducted in the USA. Results of studies indicate that parental mental illness affects the state of mental health and social networks of children. Symptomatology of children changed due to perceived social support of network contacts. Impact of social support and strong network contacts seems to depend on age of children and the family situation. That's why support offers should be adapt to children's age. Focusing on social networks as potential resource for support and needs of the family affected seems appropriate during treatment.

Privacy Breach Analysis in Social Networks

Science.gov (United States)

Nagle, Frank

This chapter addresses various aspects of analyzing privacy breaches in social networks. We first review literature that defines three types of privacy breaches in social networks: interactive, active, and passive. We then survey the various network anonymization schemes that have been constructed to address these privacy breaches. After exploring these breaches and anonymization schemes, we evaluate a measure for determining the level of anonymity inherent in a network graph based on its topological structure. Finally, we close by emphasizing the difficulty of anonymizing social network data while maintaining usability for research purposes and offering areas for future work.

Social Network Changes and Life Events across the Life Span: A Meta-Analysis

Science.gov (United States)

Wrzus, Cornelia; Hanel, Martha; Wagner, Jenny; Neyer, Franz J.

2013-01-01

For researchers and practitioners interested in social relationships, the question remains as to how large social networks typically are, and how their size and composition change across adulthood. On the basis of predictions of socioemotional selectivity theory and social convoy theory, we conducted a meta-analysis on age-related social network…

Social support and social network as intermediary social determinants of dental caries in adolescents.

Science.gov (United States)

Fontanini, Humberto; Marshman, Zoe; Vettore, Mario

2015-04-01

The aim of this study was to investigate the association between intermediary social determinants, namely social support and social network with dental caries in adolescents. An adapted version of the WHO social determinants of health conceptual framework was used to organize structural and intermediary social determinants of dental caries into six blocks including perceived social support and number of social networks. A cross-sectional study was conducted with a representative sample of 542 students between 12 and 14 years of age in public schools located in the city of Dourados, Brazil in 2012. The outcome variables were caries experience (DMFT ≥ 1) and current dental caries (component D of DMFT ≥ 1) recorded by a calibrated dentist. Individual interviews were performed to collect data on perceived social support and numbers of social networks from family and friends and covariates. Multivariate Poisson regressions using hierarchical models were conducted. The prevalence of adolescents with caries experience and current dental caries was 55.2% and 32.1%, respectively. Adolescents with low numbers of social networks and low levels of social support from family (PR 1.47; 95% CI = 1.01-2.14) were more likely to have DMFT ≥ 1. Current dental caries was associated with low numbers of social networks and low levels of social support from family (PR 2.26; 95% CI = 1.15-4.44). Social support and social network were influential psychosocial factors to dental caries in adolescents. This finding requires confirmation in other countries but potentially has implications for programmes to promote oral health. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Social network analysis for startups finding connections on the social web

CERN Document Server

Tsvetovat, Maksim

2011-01-01

Does your startup rely on social network analysis? This concise guide provides a statistical framework to help you identify social processes hidden among the tons of data now available. Social network analysis (SNA) is a discipline that predates Facebook and Twitter by 30 years. Through expert SNA researchers, you''ll learn concepts and techniques for recognizing patterns in social media, political groups, companies, cultural trends, and interpersonal networks. You''ll also learn how to use Python and other open source tools-such as NetworkX, NumPy, and Matplotlib-to gather, analyze, and vis

Contributions of Social Networking for Innovation

Directory of Open Access Journals (Sweden)

Daniela Maria Cartoni

2013-04-01

Full Text Available This paper investigates the role of virtual social networks as a mechanism complementary to formal channels of technology transfer represented by ICT and by private centers of R & D in industry. The strengthening of Web 2.0 has provided the expansion of collaborative tools, in particular the social networks, with a strong influence on the spread of knowledge and innovation. To evaluate the potential of virtual networks, a survey had been conducted to identify and describe the characteristics of some of the major social networks used in Brazil (LinkedIn, Orkut and Twitter. Even this phenomenon is not mature, the study identified the potential and benefits of social networks as informal structures that help in generation of knowledge and innovation diffusion, as a field to be explored and developed.

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

Novel Opportunistic Network Routing Based on Social Rank for Device-to-Device Communication

Directory of Open Access Journals (Sweden)

Tong Wang

2017-01-01

Full Text Available In recent years, there has been dramatic proliferation of research concerned with fifth-generation (5G mobile communication networks, among which device-to-device (D2D communication is one of the key technologies. Due to the intermittent connection of nodes, the D2D network topology may be disconnected frequently, which will lead to failure in transmission of large data files. In opportunistic networks, in case of encountering nodes which never meet before a flood message blindly to cause tremendous network overhead, a novel opportunistic network routing protocol based on social rank and intermeeting time (SRIT is proposed in this paper. An improved utility approach applied in utility replication based on encounter durations and intermeeting time is put forward to enhance the routing efficiency. Meanwhile, in order to select better candidate nodes in the network, a social graph among people is established when they socially relate to each other in social rank replication. The results under the scenario show an advantage of the proposed opportunistic network routing based on social rank and intermeeting time (SRIT over the compared algorithms in terms of delivery ratio, average delivery latency, and overhead ratio.

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.

Mental Health and Social Networks After Disaster.

Science.gov (United States)

Bryant, Richard A; Gallagher, H Colin; Gibbs, Lisa; Pattison, Philippa; MacDougall, Colin; Harms, Louise; Block, Karen; Baker, Elyse; Sinnott, Vikki; Ireton, Greg; Richardson, John; Forbes, David; Lusher, Dean

2017-03-01

Although disasters are a major cause of mental health problems and typically affect large numbers of people and communities, little is known about how social structures affect mental health after a disaster. The authors assessed the extent to which mental health outcomes after disaster are associated with social network structures. In a community-based cohort study of survivors of a major bushfire disaster, participants (N=558) were assessed for probable posttraumatic stress disorder (PTSD) and probable depression. Social networks were assessed by asking participants to nominate people with whom they felt personally close. These nominations were used to construct a social network map that showed each participant's ties to other participants they nominated and also to other participants who nominated them. This map was then analyzed for prevailing patterns of mental health outcomes. Depression risk was higher for participants who reported fewer social connections, were connected to other depressed people, or were connected to people who had left their community. PTSD risk was higher if fewer people reported being connected with the participant, if those who felt close to the participant had higher levels of property loss, or if the participant was linked to others who were themselves not interconnected. Interestingly, being connected to other people who in turn were reciprocally close to each other was associated with a lower risk of PTSD. These findings provide the first evidence of disorder-specific patterns in relation to one's social connections after disaster. Depression appears to co-occur in linked individuals, whereas PTSD risk is increased with social fragmentation. These patterns underscore the need to adopt a sociocentric perspective of postdisaster mental health in order to better understand the potential for societal interventions in the wake of disaster.

Insights into a spatially embedded social network from a large-scale snowball sample

Science.gov (United States)

Illenberger, J.; Kowald, M.; Axhausen, K. W.; Nagel, K.

2011-12-01

Much research has been conducted to obtain insights into the basic laws governing human travel behaviour. While the traditional travel survey has been for a long time the main source of travel data, recent approaches to use GPS data, mobile phone data, or the circulation of bank notes as a proxy for human travel behaviour are promising. The present study proposes a further source of such proxy-data: the social network. We collect data using an innovative snowball sampling technique to obtain details on the structure of a leisure-contacts network. We analyse the network with respect to its topology, the individuals' characteristics, and its spatial structure. We further show that a multiplication of the functions describing the spatial distribution of leisure contacts and the frequency of physical contacts results in a trip distribution that is consistent with data from the Swiss travel survey.

Contingent association between the size of the social support network and osteoporosis among Korean elderly women.

Science.gov (United States)

Lee, Seungwon; Seo, Da Hea; Kim, Kyoung Min; Lee, Eun Young; Kim, Hyeon Chang; Kim, Chang Oh; Youm, Yoosik; Rhee, Yumie

2017-01-01

To investigate the association between the number of personal ties (or the size of the social support network) and the incidence of osteoporosis among older women in Korea. Data from the Korean Urban Rural Elderly Study were used. Bone density was measured by dual-energy X-ray absorptiometry at the lumbar spine (L1-L4) and femur neck. T-score, the standardized bone density compared with what is normally expected in a healthy young adult, was measured and the presence of osteoporosis was determined, if the T-score was social support network size was measured by self-responses (number of confidants and spouse). Of the 1,846 participants, 44.9% were diagnosed with osteoporosis. The association between the social support network size and the incidence of osteoporosis was curvilinear in both bivariate and multivariate analyses. Having more people in one's social support network size was associated with lower risk of osteoporosis until it reached around four. Increasing the social support network size beyond four, in contrast, was associated with a higher risk of osteoporosis. This association was contingent on the average intimacy level of the social network. At the highest average intimacy level ("extremely close"), increasing the number of social support network members from one to six was associated with linear decrease in the predicted probability of osteoporosis from 45% to 30%. However, at the lowest average intimacy level ("not very close"), the predicted probability of osteoporosis dramatically increased from 48% to 80% as the size of the social network increased from one to six. Our results show that maintaining a large and intimate social support network is associated with a lower risk of osteoporosis among elderly Korean women, while a large but less-intimate social relationship is associated with a higher risk.

Social networking policies in nursing education.

Science.gov (United States)

Frazier, Blake; Culley, Joan M; Hein, Laura C; Williams, Amber; Tavakoli, Abbas S

2014-03-01

Social networking use has increased exponentially in the past few years. A literature review related to social networking and nursing revealed a research gap between nursing practice and education. Although there was information available on the appropriate use of social networking sites, there was limited research on the use of social networking policies within nursing education. The purpose of this study was to identify current use of social media by faculty and students and a need for policies within nursing education at one institution. A survey was developed and administered to nursing students (n = 273) and nursing faculty (n = 33). Inferential statistics included χ², Fisher exact test, t test, and General Linear Model. Cronbach's α was used to assess internal consistency of social media scales. The χ² result indicates that there were associations with the group and several social media items. t Test results indicate significant differences between student and faculty for average of policies are good (P = .0127), policies and discipline (P = .0315), and policy at the study school (P = .0013). General Linear Model analyses revealed significant differences for "friend" a patient with a bond, unprofessional posts, policy, and nursing with class level. Results showed that students and faculty supported the development of a social networking policy.

The Strategic Paradox of Social Networks

Science.gov (United States)

2011-03-18

United States claimed to have met online.9 And in 2010, Facebook claimed over 500 million users, which would make the social networking service the...service culture, or occupational specialty. One drawback with social networks concerns the protection of individual privacy. Facebook , for...St ra te gy R es ea rc h Pr oj ec t THE STRATEGIC PARADOX OF SOCIAL NETWORKS BY COLONEL ROBERT COTE United States Marine Corps

Large scale network-centric distributed systems

CERN Document Server

Sarbazi-Azad, Hamid

2014-01-01

A highly accessible reference offering a broad range of topics and insights on large scale network-centric distributed systems Evolving from the fields of high-performance computing and networking, large scale network-centric distributed systems continues to grow as one of the most important topics in computing and communication and many interdisciplinary areas. Dealing with both wired and wireless networks, this book focuses on the design and performance issues of such systems. Large Scale Network-Centric Distributed Systems provides in-depth coverage ranging from ground-level hardware issu

The Social Origins of Networks and Diffusion.

Science.gov (United States)

Centola, Damon

2015-03-01

Recent research on social contagion has demonstrated significant effects of network topology on the dynamics of diffusion. However, network topologies are not given a priori. Rather, they are patterns of relations that emerge from individual and structural features of society, such as population composition, group heterogeneity, homophily, and social consolidation. Following Blau and Schwartz, the author develops a model of social network formation that explores how social and structural constraints on tie formation generate emergent social topologies and then explores the effectiveness of these social networks for the dynamics of social diffusion. Results show that, at one extreme, high levels of consolidation can create highly balkanized communities with poor integration of shared norms and practices. As suggested by Blau and Schwartz, reducing consolidation creates more crosscutting circles and significantly improves the dynamics of social diffusion across the population. However, the author finds that further reducing consolidation creates highly intersecting social networks that fail to support the widespread diffusion of norms and practices, indicating that successful social diffusion can depend on moderate to high levels of structural consolidation.

The social support and social network characteristics of smokers in methadone maintenance treatment.

Science.gov (United States)

de Dios, Marcel Alejandro; Stanton, Cassandra A; Caviness, Celeste M; Niaura, Raymond; Stein, Michael

2013-01-01

Previous studies have shown social support and social network variables to be important factors in smoking cessation treatment. Tobacco use is highly prevalent among individuals in methadone maintenance treatment (MMT). However, smoking cessation treatment outcomes in this vulnerable subpopulation have been poor and social support and social network variables may contribute. The current study examined the social support and social network characteristics of 151 MMT smokers involved in a randomized clinical trial of smoking cessation treatments. Participants were 50% women and 78% Caucasian. A high proportion (57%) of MMT smokers had spouses or partners who smoke and over two-thirds of households (68.5%) included at least one smoker. Our sample was characterized by relatively small social networks, but high levels of general social support and quitting support. The number of cigarettes per day was found to be positively associated with the number of smokers in the social network (r = .239, p social support and social networks of smokers in MMT.

Social network analysis and supply chain management

Directory of Open Access Journals (Sweden)

Raúl Rodríguez Rodríguez

2016-01-01

Full Text Available This paper deals with social network analysis and how it could be integrated within supply chain management from a decision-making point of view. Even though the benefits of using social analysis have are widely accepted at both academic and industry/services context, there is still a lack of solid frameworks that allow decision-makers to connect the usage and obtained results of social network analysis – mainly both information and knowledge flows and derived results- with supply chain management objectives and goals. This paper gives an overview of social network analysis, the main social network analysis metrics, supply chain performance and, finally, it identifies how future frameworks could close the gap and link the results of social network analysis with the supply chain management decision-making processes.

Use intensity of social networks in southern Brazil

Directory of Open Access Journals (Sweden)

Rafaele Matte Wojahn

2017-08-01

Full Text Available A social network implies in connect people. This article aims to identify the use intensity of social network in Southern Brazil. The research was characterized by quantitative approach, descriptive, cross-sectional and survey, with a sample of 372 respondents. To data analysis was used descriptive analysis to characterize the sample, verify the access frequency of social networks and the daily access time, and Pearson’s Correlation to identify the daily access time and the social networks. The results indicated the social network used in more intensity is the Facebook and then Whatsapp, and the access occurs at home. However, all the social networks promote interactions toward users.

The Social Life of Social Networks

DEFF Research Database (Denmark)

Robertson, Scott P.; Vatrapu, Ravi; Medina, Richard

2009-01-01

dialogues wished to send other participants. We show a strong integration of the Web 2.0 and new media technologies of social networking, online video, and blogs. Outside of video content, users tended to direct others to groups and applications within the Facebook community, but this homophilous behavior......This paper examines the linkage patterns of people who posted links on the Facebook “walls” of Barack Obama, Hillary Clinton, and John McCain over two years prior to the 2008 U.S. Presidential election. Linkage patterns indicate the destinations to which participants in these social networking...

[Social networks and medicine].

Science.gov (United States)

Bastardot, F; Vollenweider, P; Marques-Vidal, P

2015-11-04

Social networks (social media or #SoMe) have entered medical practice within the last few years. These new media--like Twitter or Skype--enrich interactions among physicians (telemedicine), among physicians and patients (virtual consultations) and change the way of teaching medicine. They also entail new ethical, deontological and legal issues: the extension of the consultation area beyond the medical office and the access of information by third parties were recently debated. We develop here a review of some social networks with their characteristics, applications for medicine and limitations, and we offer some recommendations of good practice.

Analysing the Correlation between Social Network Analysis Measures and Performance of Students in Social Network-Based Engineering Education

Science.gov (United States)

Putnik, Goran; Costa, Eric; Alves, Cátia; Castro, Hélio; Varela, Leonilde; Shah, Vaibhav

2016-01-01

Social network-based engineering education (SNEE) is designed and implemented as a model of Education 3.0 paradigm. SNEE represents a new learning methodology, which is based on the concept of social networks and represents an extended model of project-led education. The concept of social networks was applied in the real-life experiment,…

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.

Personal social networks and organizational affiliation of South Asians in the United States.

Science.gov (United States)

Kandula, Namratha R; Cooper, Andrew J; Schneider, John A; Fujimoto, Kayo; Kanaya, Alka M; Van Horn, Linda; deKoning, Lawrence; Siddique, Juned

2018-02-05

Understanding the social lives of South Asian immigrants in the United States (U.S) and their influence on health can inform interpersonal and community-level health interventions for this growing community. This paper describe the rationale, survey design, measurement, and network properties of 700 South Asian individuals in the Mediators of Atherosclerosis in South Asians Living in America (MASALA) social networks ancillary study. MASALA is a community-based cohort, established in 2010, to understand risk factors for cardiovascular disease among South Asians living in the U.S. Survey data collection on personal social networks occurred between 2014 and 2017. Network measurements included size, composition, density, and organizational affiliations. Data on participants' self-rated health and social support functions and health-related discussions among network members were also collected. Participants' age ranged from 44 to 84 (average 59 years), and 57% were men. South Asians had large (size=5.6, SD=2.6), kin-centered (proportion kin=0.71, SD=0.28), and dense networks. Affiliation with religious and spiritual organizations was perceived as beneficial to health. Emotional closeness with network members was positively associated with participants' self-rated health (p-value networks with higher density and more kin were significantly associated with health-related discussions. The MASALA networks study advances research on the cultural patterning of social relationships and sources of social support in South Asians living in the U.S. Future analyses will examine how personal social networks and organizational affiliations influence South Asians' health behaviors and outcomes. ClinicalTrials.gov identifier: NCT02268513.

Knowledge Strategies in Using Social Networks

Directory of Open Access Journals (Sweden)

Contantin BRĂTIANU

2013-05-01

Full Text Available Knowledge strategy selection is a multiple criteria decision-making (MCDM problem, and requires adequate methods to solve it appropriately. Knowledge strategies are also intrinsically linked to individuals and their ability to comprehend the world and leverage their intellectual assets to respond e!ectively to a fast changing environment. the essential features of social networking sites include but are not limited to: blogging, grouping, networking and instant messaging. Since the social networks facilitate communication and interaction among users, there is a continuous need of researches to examine what are the motives that a!ect the acceptance of usage of the social networks. This study aims at examining the role of the knowledge strategies that individuals employ in using social networks with respect to the overall objective of increasing the knowledge level. For this purpose we have used the Analytic Hierarchy Process (AHP mathematical model since it allows us a structuring of the overall objective on the main components. For the present research we considered a structure composed of three levels: L1 – the purpose of networking, L2 – strategies used to achieve that purpose, and L3 – activities needed for strategies implementation. At the upper level (L1, the main objective of a person in using social networks is to increase its knowledge level. To obtain the aforementioned objective we considered for the second level (L2 the following strategies: S1 – to learn from other persons; S2 – to make new friends; S3 – to increase the personal experience and visibility. the implementation of these strategies is realized through the following activities considered at the third hierarchy level (L3: A1– joining general social networks (e.g. Facebook, Google+, MySpace, Hi5 etc.; A2– joining professional social networks (e.g. LinkedIn etc.; A3– creating a personal blog (e.g. Blogster, Wordpress etc.; A4– joining online communities of

PRIVACY PROTECTION PROBLEMS IN SOCIAL NETWORKS

OpenAIRE

OKUR, M. Cudi

2011-01-01

Protecting privacy has become a major concern for most social network users because of increased difficulties of controlling the online data. This article presents an assessment of the common privacy related risks of social networking sites. Open and hidden privacy risks of active and passive online profiles are examined and increasing share of social networking in these phenomena is discussed. Inadequacy of available legal and institutional protection is demonstrated and the effectiveness of...

Social Support Networks Among Diverse Sexual Minority Populations

Science.gov (United States)

Frost, David M.; Meyer, Ilan H.; Schwartz, Sharon

2016-01-01

This paper reports a study of the function and composition of social support networks among diverse lesbian, gay and bisexual (LGB) men and women (n = 396) in comparison to their heterosexual peers (n = 128). Data were collected using a structured social support network matrix in a community sample recruited in New York City. Our findings show that gay and bisexual men may rely on “chosen families” within LGBT communities more so than lesbian and bisexual women. Both heterosexuals and LGBs relied less on family and more on other people (e.g., friends, co-workers) for everyday social support (e.g., recreational and social activities, talking about problems). Providers of everyday social support were most often of the same sexual orientation and race/ethnicity as participants. In seeking major support (e.g., borrowing large sums of money), heterosexual men and women along with lesbian and bisexual women relied primarily on their families, but gay and bisexual men relied primarily on other LGB individuals. Racial/ethnic minority LGBs relied on LGB similar others at the same rate at White LGBs but, notably, racial/ethnic minority LGBs reported receiving fewer dimensions of support. PMID:26752447

Social network analysis of study environment

Directory of Open Access Journals (Sweden)

Blaženka Divjak

2010-06-01

Full Text Available Student working environment influences student learning and achievement level. In this respect social aspects of students’ formal and non-formal learning play special role in learning environment. The main research problem of this paper is to find out if students' academic performance influences their position in different students' social networks. Further, there is a need to identify other predictors of this position. In the process of problem solving we use the Social Network Analysis (SNA that is based on the data we collected from the students at the Faculty of Organization and Informatics, University of Zagreb. There are two data samples: in the basic sample N=27 and in the extended sample N=52. We collected data on social-demographic position, academic performance, learning and motivation styles, student status (full-time/part-time, attitudes towards individual and teamwork as well as informal cooperation. Afterwards five different networks (exchange of learning materials, teamwork, informal communication, basic and aggregated social network were constructed. These networks were analyzed with different metrics and the most important were betweenness, closeness and degree centrality. The main result is, firstly, that the position in a social network cannot be forecast only by academic success and, secondly, that part-time students tend to form separate groups that are poorly connected with full-time students. In general, position of a student in social networks in study environment can influence student learning as well as her/his future employability and therefore it is worthwhile to be investigated.

Controlling nosocomial infection based on structure of hospital social networks.

Science.gov (United States)

Ueno, Taro; Masuda, Naoki

2008-10-07

Nosocomial infection (i.e. infection in healthcare facilities) raises a serious public health problem, as implied by the existence of pathogens characteristic to healthcare facilities such as methicillin-resistant Staphylococcus aureus and hospital-mediated outbreaks of influenza and severe acute respiratory syndrome. For general communities, epidemic modeling based on social networks is being recognized as a useful tool. However, disease propagation may occur in a healthcare facility in a manner different from that in a urban community setting due to different network architecture. We simulate stochastic susceptible-infected-recovered dynamics on social networks, which are based on observations in a hospital in Tokyo, to explore effective containment strategies against nosocomial infection. The observed social networks in the hospital have hierarchical and modular structure in which dense substructure such as departments, wards, and rooms, are globally but only loosely connected, and do not reveal extremely right-skewed distributions of the number of contacts per individual. We show that healthcare workers, particularly medical doctors, are main vectors (i.e. transmitters) of diseases on these networks. Intervention methods that restrict interaction between medical doctors and their visits to different wards shrink the final epidemic size more than intervention methods that directly protect patients, such as isolating patients in single rooms. By the same token, vaccinating doctors with priority rather than patients or nurses is more effective. Finally, vaccinating individuals with large betweenness centrality (frequency of mediating connection between pairs of individuals along the shortest paths) is superior to vaccinating ones with large connectedness to others or randomly chosen individuals, which was suggested by previous model studies.

Social Networking Adapted for Distributed Scientific Collaboration

Science.gov (United States)

Karimabadi, Homa

2012-01-01

Share is a social networking site with novel, specially designed feature sets to enable simultaneous remote collaboration and sharing of large data sets among scientists. The site will include not only the standard features found on popular consumer-oriented social networking sites such as Facebook and Myspace, but also a number of powerful tools to extend its functionality to a science collaboration site. A Virtual Observatory is a promising technology for making data accessible from various missions and instruments through a Web browser. Sci-Share augments services provided by Virtual Observatories by enabling distributed collaboration and sharing of downloaded and/or processed data among scientists. This will, in turn, increase science returns from NASA missions. Sci-Share also enables better utilization of NASA s high-performance computing resources by providing an easy and central mechanism to access and share large files on users space or those saved on mass storage. The most common means of remote scientific collaboration today remains the trio of e-mail for electronic communication, FTP for file sharing, and personalized Web sites for dissemination of papers and research results. Each of these tools has well-known limitations. Sci-Share transforms the social networking paradigm into a scientific collaboration environment by offering powerful tools for cooperative discourse and digital content sharing. Sci-Share differentiates itself by serving as an online repository for users digital content with the following unique features: a) Sharing of any file type, any size, from anywhere; b) Creation of projects and groups for controlled sharing; c) Module for sharing files on HPC (High Performance Computing) sites; d) Universal accessibility of staged files as embedded links on other sites (e.g. Facebook) and tools (e.g. e-mail); e) Drag-and-drop transfer of large files, replacing awkward e-mail attachments (and file size limitations); f) Enterprise-level data and

Do social networks affect the use of residential aged care among older Australians?

Directory of Open Access Journals (Sweden)

Glonek Gary FV

2007-10-01

Full Text Available Abstract Background Older people's social networks with family and friends can affect residential aged care use. It remains unclear if there are differences in the effects of specific (with children, other relatives, friends and confidants and total social networks upon use of low-level residential care and nursing homes. Methods Data were drawn from the Australian Longitudinal Study of Ageing. Six waves of data from 1477 people aged ≥ 70 collected over nine years of follow-up were used. Multinomial logistic regressions of the effects of specific and total social networks on residential care use were carried out. Propensity scores were used in the analyses to adjust for differences in participant's health, demographic and lifestyle characteristics with respect to social networks. Results Higher scores for confidant networks were protective against nursing home use (odds ratio [OR] upper versus lower tertile of confidant networks = 0.50; 95%CI 0.33–0.75. Similarly, a significant effect of upper versus lower total network tertile on nursing home use was observed (OR = 0.62; 95%CI 0.43–0.90. Evidence of an effect of children networks on nursing home use was equivocal. Nursing home use was not predicted by other relatives or friends social networks. Use of lower-level residential care was unrelated to social networks of any type. Social networks of any type did not have a significant effect upon low-level residential care use. Discussion Better confidant and total social networks predict nursing home use in a large cohort of older Australians. Policy needs to reflect the importance of these particular relationships in considering where older people want to live in the later years of life.

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.

Sci-Share: Social Networking Adapted for Distributed Scientific Collaboration, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Our goal is to develop a social networking site with novel, specially designed feature sets to enable simultaneous remote collaboration and sharing of large data...

Consumer Activities and Reactions to Social Network Marketing

Directory of Open Access Journals (Sweden)

Bistra Vassileva

2017-06-01

Full Text Available The purpose of this paper is to understand consumer behavioural models with respect to their reactions to social network marketing. Theoretical background is focused on online and social network usage, motivations and behaviour. The research goal is to explore consumer reactions to the exposure of social network marketing based on the following criteria: level of brand engagement, word-of-mouth (WOM referral behaviour, and purchase intentions. Consumers are investigated based on their attitudes toward social network marketing and basic socio-demographic covariates using data from a sample size of 700 Bulgarian respondents (age group 21–54 years, Internet users, urban inhabitants. Factor and cluster analyses are applied. It is found that consumers are willing to receive information about brands and companies through social networks. They like to talk in social networks about these brands and companies and to share information as well (factor 2, brand engagement. Internet users are willing to share information received through social network advertising (factor 1, wom referral behaviour but they would not buy a certain brand as a result of brand communication activities in social networks (factor 3, purchase intention. Several practical implications regarding marketing activities through social networks are drawn.

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.

Statistical Models for Social Networks

NARCIS (Netherlands)

Snijders, Tom A. B.; Cook, KS; Massey, DS

2011-01-01

Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For

Social Support and Social Networks in COPD: A Scoping Review.

Science.gov (United States)

Barton, Christopher; Effing, Tanya W; Cafarella, Paul

2015-01-01

A scoping review was conducted to determine the size and nature of the evidence describing associations between social support and networks on health, management and clinical outcomes amongst patients with COPD. Searches of PubMed, PsychInfo and CINAHL were undertaken for the period 1966-December 2013. A descriptive synthesis of the main findings was undertaken to demonstrate where there is current evidence for associations between social support, networks and health outcomes, and where further research is needed. The search yielded 318 papers of which 287 were excluded after applying selection criteria. Two areas emerged in which there was consistent evidence of benefit of social support; namely mental health and self-efficacy. There was inconsistent evidence for a relationship between perceived social support and quality of life, physical functioning and self-rated health. Hospital readmission was not associated with level of perceived social support. Only a small number of studies (3 articles) have reported on the social network of individuals with COPD. There remains a need to identify the factors that promote and enable social support. In particular, there is a need to further understand the characteristics of social networks within the broader social structural conditions in which COPD patients live and manage their illness.

Age and Gender Differences in Social Network Composition and Social Support Among Older Rural South Africans: Findings From the HAALSI Study.

Science.gov (United States)

Harling, Guy; Morris, Katherine Ann; Manderson, Lenore; Perkins, Jessica M; Berkman, Lisa F

2018-03-26

Drawing on the "Health and Aging in Africa: A Longitudinal Study of an INDEPTH community in South Africa" (HAALSI) baseline survey, we present data on older adults' social networks and receipt of social support in rural South Africa. We examine how age and gender differences in social network characteristics matched with patterns predicted by theories of choice- and constraint-based network contraction in older adults. We used regression analysis on data for 5,059 South African adults aged 40 and older. Older respondents reported fewer important social contacts and less frequent communication than their middle-aged peers, largely due to fewer nonkin connections. Network size difference between older and younger respondents was greater for women than for men. These gender and age differences were explicable by much higher levels of widowhood among older women compared to younger women and older men. There was no evidence for employment-related network contraction or selective retention of emotionally supportive ties. Marriage-related structural constraints impacted on older women's social networks in rural South Africa, but did not explain choice-based network contraction. These findings suggest that many older women in rural Africa, a growing population, may have an unmet need for social support.

Regional Use of Social Networking Tools

Science.gov (United States)

2014-12-01

4 2.1.7 Tumblr 4 2.1.8 Instagram 4 2.2 Local Social Networking Services 5 3 Regional Preferences for Social Networking Tools 6 4 African Region...YouTube 280 million Twitter 255 million LinkedIn n/a Pinterest n/a Tumblr 300 million Instagram 200 million The active-user base numbers...so this percentage may decline in the future. 2.1.8 Instagram Instagram , acquired by Facebook in 2012, is a mobile social networking service that

Social networks and human development / Redes sociales y desarrollo humano

Directory of Open Access Journals (Sweden)

Sara Gallego Trijueque

2011-10-01

Full Text Available The aim of this work is a brief introduction to the concept of social networks and their importance in society. Social networks have been responsible over the centuries to preserve community values, in addition to being facilitators of social interaction in human development processes, through communication and relationships between individuals.

Computational Social Network Analysis

CERN Document Server

Hassanien, Aboul-Ella

2010-01-01

Presents insight into the social behaviour of animals (including the study of animal tracks and learning by members of the same species). This book provides web-based evidence of social interaction, perceptual learning, information granulation and the behaviour of humans and affinities between web-based social networks

Business socialising: women’s social networking perceptions

OpenAIRE

13104802 - Bogaards, Marlene; Mostert, Karina; 10868445 - De Klerk, Saskia

2012-01-01

The primary research objective of the study was to investigate the perceptions of the social networking practices of businesswomen. A non-probability purposive voluntary sample, followed by snowball sampling, was used to select businesswomen (n = 31) living and working in the Gauteng province for in-depth interviews. Various perceptions of businesswomen of social networking practices were identified. A number of networking challenges that businesswomen experience in their social networking ef...

Review of Social Networking Sites' Security and Privacy

OpenAIRE

YANG, SHUN

2015-01-01

Nowadays social media networking has dramatically increased. Social networking sites like Facebook make users create huge amount of profiles and share personal information within networking of different users. Social networking exposes personal information far beyond the group of friends. And that information or data on social media networking could be potential threat to people's information security and privacy. In this review, we are going to view the privacy risks and security problem...

Second-Order Assortative Mixing in Social Networks

DEFF Research Database (Denmark)

Zhou, Shi; Cox, Ingemar; Hansen, Lars Kai

2017-01-01

In a social network, the number of links of a node, or node degree, is often assumed as a proxy for the node’s importance or prominence within the network. It is known that social networks exhibit the (first-order) assortative mixing, i.e. if two nodes are connected, they tend to have similar node...... degrees, suggesting that people tend to mix with those of comparable prominence. In this paper, we report the second-order assortative mixing in social networks. If two nodes are connected, we measure the degree correlation between their most prominent neighbours, rather than between the two nodes...... themselves. We observe very strong second-order assortative mixing in social networks, often significantly stronger than the first-order assortative mixing. This suggests that if two people interact in a social network, then the importance of the most prominent person each knows is very likely to be the same...

Organizational Application of Social Networking Information Technologies

Science.gov (United States)

Reppert, Jeffrey R.

2012-01-01

The focus of this qualitative research study using the Delphi method is to provide a framework for leaders to develop their own social networks. By exploring concerns in four areas, leaders may be able to better plan, implement, and manage social networking systems in organizations. The areas addressed are: (a) social networking using…

HOW DO STUDENTS SELECT SOCIAL NETWORKING SITES? AN ANALYTIC HIERARCHY PROCESS (AHP MODEL

Directory of Open Access Journals (Sweden)

Chun Meng Tang

2015-12-01

Full Text Available Social networking sites are popular among university students, and students today are indeed spoiled for choice. New emerging social networking sites sprout up amid popular sites, while some existing ones die out. Given the choice of so many social networking sites, how do students decide which one they will sign up for and stay on as an active user? The answer to this question is of interest to social networking site designers and marketers. The market of social networking sites is highly competitive. To maintain the current user base and continue to attract new users, how should social networking sites design their sites? Marketers spend a fairly large percent of their marketing budget on social media marketing. To formulate an effective social media strategy, how much do marketers understand the users of social networking sites? Learning from website evaluation studies, this study intends to provide some answers to these questions by examining how university students decide between two popular social networking sites, Facebook and Twitter. We first developed an analytic hierarchy process (AHP model of four main selection criteria and 12 sub-criteria, and then administered a questionnaire to a group of university students attending a course at a Malaysian university. AHP analyses of the responses from 12 respondents provided an insight into the decision-making process involved in students’ selection of social networking sites. It seemed that of the four main criteria, privacy was the top concern, followed by functionality, usability, and content. The sub-criteria that were of key concern to the students were apps, revenue-generating opportunities, ease of use, and information security. Between Facebook and Twitter, the students thought that Facebook was the better choice. This information is useful for social networking site designers to design sites that are more relevant to their users’ needs, and for marketers to craft more effective

Network interventions - How citizens’ social media networks influence their political participation

DEFF Research Database (Denmark)

Ohme, Jakob; de Vreese, Claes Holger; Albæk, Erik

Social media platforms are special places of information exposure because they are structured around a user’s social network and not around content, like other news media. Studies could show that news exposure on social media can affect citizens’ political participation due to the personalized......, targeted, & inadvertent exposure. However, previous research did not strongly focus on how the characteristics of a citizens’ social media network might alter this relationship. We tests how political information exposure via three different media channels affects political participation among Danish...... citizens and examine possible moderation effects of users network size, network diversity and the newly introduced parameter of perceived network activity. To this end, a two-wave online survey (n=858) among the Danish population was conducted, applying a smartphone-based media diary study. We find strong...

Social Media and Social Networking Applications for Teaching and Learning

Science.gov (United States)

Yeo, Michelle Mei Ling

2014-01-01

This paper aims to better understand the experiences of the youth and the educators with the tapping of social media like YouTube videos and the social networking application of Facebook for teaching and learning. This paper is interested in appropriating the benefits of leveraging of social media and networking applications like YouTube and…

Benefits of Enterprise Social Networking Systems for High Energy Physics community

Science.gov (United States)

Silva de Sousa, B.; Wagner, A.; Ormancey, E.; Grzywaczewski, P.

2015-12-01

The emergence of social media platforms in the consumer space unlocked new ways of interaction between individuals on the Web. People develop now their social networks and relations based on common interests and activities with the choice to opt-in or opt-out on content of their interest. This kind of platforms have also an important place to fill inside large organizations and enterprises where communication and collaborators interaction are keys for development. Enterprise Social Networking Systems (ESN) add value to an organization by encouraging information sharing, capturing knowledge, enabling action and empowering people. CERN is currently rolling out an ESN which aims to unify and provide a single point of access to the multitude of information sources in the organization. It also implements social features that can be added on top of existing communication channels. While the deployment of this kind of platforms is not without risks we firmly believe that they are of the best interest for our community, opening the opportunity to evaluate a global social network for High Energy Physics (HEP).

Socio-Cognitive Phenotypes Differentially Modulate Large-Scale Structural Covariance Networks.

Science.gov (United States)

Valk, Sofie L; Bernhardt, Boris C; Böckler, Anne; Trautwein, Fynn-Mathis; Kanske, Philipp; Singer, Tania

2017-02-01

Functional neuroimaging studies have suggested the existence of 2 largely distinct social cognition networks, one for theory of mind (taking others' cognitive perspective) and another for empathy (sharing others' affective states). To address whether these networks can also be dissociated at the level of brain structure, we combined behavioral phenotyping across multiple socio-cognitive tasks with 3-Tesla MRI cortical thickness and structural covariance analysis in 270 healthy adults, recruited across 2 sites. Regional thickness mapping only provided partial support for divergent substrates, highlighting that individual differences in empathy relate to left insular-opercular thickness while no correlation between thickness and mentalizing scores was found. Conversely, structural covariance analysis showed clearly divergent network modulations by socio-cognitive and -affective phenotypes. Specifically, individual differences in theory of mind related to structural integration between temporo-parietal and dorsomedial prefrontal regions while empathy modulated the strength of dorsal anterior insula networks. Findings were robust across both recruitment sites, suggesting generalizability. At the level of structural network embedding, our study provides a double dissociation between empathy and mentalizing. Moreover, our findings suggest that structural substrates of higher-order social cognition are reflected rather in interregional networks than in the the local anatomical markup of specific regions per se. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A new centrality measure for identifying influential nodes in social networks

Science.gov (United States)

Rhouma, Delel; Ben Romdhane, Lotfi

2018-04-01

The identification of central nodes has been a key problem in the field of social network analysis. In fact, it is a measure that accounts the popularity or the visibility of an actor within a network. In order to capture this concept, various measures, either sample or more elaborate, has been developed. Nevertheless, many of "traditional" measures are not designed to be applicable to huge data. This paper sets out a new node centrality index suitable for large social network. It uses the amount of the neighbors of a node and connections between them to characterize a "pivot" node in the graph. We presented experimental results on real data sets which show the efficiency of our proposal.

Social networking for well-being

NARCIS (Netherlands)

Steen, M.G.D.; Aarts, O.A.J.; Broekman, C.C.M.T.; Prins, S.C.L.

2011-01-01

In this paper, we present some of the work that is being done in the WeCare project (in the AAL programme). The project’s goal is to introduce social networking services in the lives of older people, in order to improve their well-being. Participation in social networks, both online and ‘in real

Public Spheres and Mediated Social Networks in the Western Context and Beyond

OpenAIRE

Wheeler, Mark; Iosifidis, Petros

2016-01-01

Social media is said to radically change the way in which public communication takes place: information diffuses faster and can reach a large number of people, but what makes the process so novel is that online networks can empower people to compete with traditional broadcasters or public figures. This book critically interrogates the contemporary relevance of social networks as a set of economic, cultural and political enterprises and as a public sphere in which a variety of political and so...

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.

Identifying influential nodes in large-scale directed networks: the role of clustering.

Science.gov (United States)

Chen, Duan-Bing; Gao, Hui; Lü, Linyuan; Zhou, Tao

2013-01-01

Identifying influential nodes in very large-scale directed networks is a big challenge relevant to disparate applications, such as accelerating information propagation, controlling rumors and diseases, designing search engines, and understanding hierarchical organization of social and biological networks. Known methods range from node centralities, such as degree, closeness and betweenness, to diffusion-based processes, like PageRank and LeaderRank. Some of these methods already take into account the influences of a node's neighbors but do not directly make use of the interactions among it's neighbors. Local clustering is known to have negative impacts on the information spreading. We further show empirically that it also plays a negative role in generating local connections. Inspired by these facts, we propose a local ranking algorithm named ClusterRank, which takes into account not only the number of neighbors and the neighbors' influences, but also the clustering coefficient. Subject to the susceptible-infected-recovered (SIR) spreading model with constant infectivity, experimental results on two directed networks, a social network extracted from delicious.com and a large-scale short-message communication network, demonstrate that the ClusterRank outperforms some benchmark algorithms such as PageRank and LeaderRank. Furthermore, ClusterRank can also be applied to undirected networks where the superiority of ClusterRank is significant compared with degree centrality and k-core decomposition. In addition, ClusterRank, only making use of local information, is much more efficient than global methods: It takes only 191 seconds for a network with about [Formula: see text] nodes, more than 15 times faster than PageRank.

Identifying influential nodes in large-scale directed networks: the role of clustering.

Directory of Open Access Journals (Sweden)

Duan-Bing Chen

Full Text Available Identifying influential nodes in very large-scale directed networks is a big challenge relevant to disparate applications, such as accelerating information propagation, controlling rumors and diseases, designing search engines, and understanding hierarchical organization of social and biological networks. Known methods range from node centralities, such as degree, closeness and betweenness, to diffusion-based processes, like PageRank and LeaderRank. Some of these methods already take into account the influences of a node's neighbors but do not directly make use of the interactions among it's neighbors. Local clustering is known to have negative impacts on the information spreading. We further show empirically that it also plays a negative role in generating local connections. Inspired by these facts, we propose a local ranking algorithm named ClusterRank, which takes into account not only the number of neighbors and the neighbors' influences, but also the clustering coefficient. Subject to the susceptible-infected-recovered (SIR spreading model with constant infectivity, experimental results on two directed networks, a social network extracted from delicious.com and a large-scale short-message communication network, demonstrate that the ClusterRank outperforms some benchmark algorithms such as PageRank and LeaderRank. Furthermore, ClusterRank can also be applied to undirected networks where the superiority of ClusterRank is significant compared with degree centrality and k-core decomposition. In addition, ClusterRank, only making use of local information, is much more efficient than global methods: It takes only 191 seconds for a network with about [Formula: see text] nodes, more than 15 times faster than PageRank.

Identifying Influential Nodes in Large-Scale Directed Networks: The Role of Clustering

Science.gov (United States)

Chen, Duan-Bing; Gao, Hui; Lü, Linyuan; Zhou, Tao

2013-01-01

Identifying influential nodes in very large-scale directed networks is a big challenge relevant to disparate applications, such as accelerating information propagation, controlling rumors and diseases, designing search engines, and understanding hierarchical organization of social and biological networks. Known methods range from node centralities, such as degree, closeness and betweenness, to diffusion-based processes, like PageRank and LeaderRank. Some of these methods already take into account the influences of a node’s neighbors but do not directly make use of the interactions among it’s neighbors. Local clustering is known to have negative impacts on the information spreading. We further show empirically that it also plays a negative role in generating local connections. Inspired by these facts, we propose a local ranking algorithm named ClusterRank, which takes into account not only the number of neighbors and the neighbors’ influences, but also the clustering coefficient. Subject to the susceptible-infected-recovered (SIR) spreading model with constant infectivity, experimental results on two directed networks, a social network extracted from delicious.com and a large-scale short-message communication network, demonstrate that the ClusterRank outperforms some benchmark algorithms such as PageRank and LeaderRank. Furthermore, ClusterRank can also be applied to undirected networks where the superiority of ClusterRank is significant compared with degree centrality and k-core decomposition. In addition, ClusterRank, only making use of local information, is much more efficient than global methods: It takes only 191 seconds for a network with about nodes, more than 15 times faster than PageRank. PMID:24204833

Critical Transitions in Social Network Activity

DEFF Research Database (Denmark)

Kuehn, Christian; Martens, Erik Andreas; Romero, Daniel M

2014-01-01

A large variety of complex systems in ecology, climate science, biomedicine and engineering have been observed to exhibit tipping points, where the dynamical state of the system abruptly changes. For example, such critical transitions may result in the sudden change of ecological environments...... a priori known events are preceded by variance and autocorrelation growth. Our findings thus clearly establish the necessary starting point to further investigate the relationship between abstract mathematical theory and various classes of critical transitions in social networks....

Social networks and factor markets

DEFF Research Database (Denmark)

Abay, Kibrom Araya; Kahsay, Goytom Abraha; Berhane, Guush

In the absence of well-established factor markets, the role of indigenous institutions and social networks can be substantial for mobilizing factors for agricultural production. We investigate the role of an indigenous social network in Ethiopia, the iddir, in facilitating factor market...... transactions among smallholder farmers. Using detailed longitudinal household survey data and employing a difference-in-differences approach, we find that iddir membership improves households’ access to factor markets. Specifically, we find that joining an iddir network improves households’ access to land...

Adoption of Social Networking in Education: A Study of the Use of Social Networks by Higher Education Students in Oman

Science.gov (United States)

Al-Mukhaini, Elham M.; Al-Qayoudhi, Wafa S.; Al-Badi, Ali H.

2014-01-01

The use of social networks is a growing phenomenon, being increasingly important in both private and academic life. Social networks are used as tools to enable users to have social interaction. The use of social networks (SNs) complements and enhances the teaching in traditional classrooms. For example, YouTube, Facebook, wikis, and blogs provide…

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…

Brain networks of social comparison.

Science.gov (United States)

Kedia, Gayannée; Lindner, Michael; Mussweiler, Thomas; Ihssen, Niklas; Linden, David E J

2013-03-27

Social comparison, that is, the process of comparing oneself to other people, is a ubiquitous social cognitive mechanism; however, so far its neural correlates have remained unknown. The present study tested the hypothesis that social comparisons are supported by partly dissociated networks, depending on whether the dimension under comparison concerns a physical or a psychological attribute. We measured brain activity with functional MRI, whereas participants were comparing their own height or intelligence to that of individuals they personally know. Height comparisons were associated with higher activity in a frontoparietal network involved in spatial and numerical cognition. Conversely, intelligence comparisons recruited a network of midline areas that have been previously implicated in the attribution of mental states to oneself and others (Theory of mind). These findings suggest that social comparisons rely on diverse domain-specific mechanisms rather than on one unitary process.

Activity-Driven Influence Maximization in Social Networks

DEFF Research Database (Denmark)

Kumar, Rohit; Saleem, Muhammad Aamir; Calders, Toon

2017-01-01

-driven approach based on the identification of influence propagation patterns. In the first work, we identify so-called information-channels to model potential pathways for information spread, while the second work exploits how users in a location-based social network check in to locations in order to identify...... influential locations. To make our algorithms scalable, approximate versions based on sketching techniques from the data streams domain have been developed. Experiments show that in this way it is possible to efficiently find good seed sets for influence propagation in social networks.......Interaction networks consist of a static graph with a timestamped list of edges over which interaction took place. Examples of interaction networks are social networks whose users interact with each other through messages or location-based social networks where people interact by checking...

Social network analysis community detection and evolution

CERN Document Server

Missaoui, Rokia

2015-01-01

This book is devoted to recent progress in social network analysis with a high focus on community detection and evolution. The eleven chapters cover the identification of cohesive groups, core components and key players either in static or dynamic networks of different kinds and levels of heterogeneity. Other important topics in social network analysis such as influential detection and maximization, information propagation, user behavior analysis, as well as network modeling and visualization are also presented. Many studies are validated through real social networks such as Twitter. This edit

Social networks and bronchial asthma.

Science.gov (United States)

D'Amato, Gennaro; Cecchi, Lorenzo; Liccardi, Gennaro; D'Amato, Maria; Stanghellini, Giovanni

2013-02-01

To focus on both positive and negative aspects of the interaction between asthmatic patients and the social networks, and to highlight the need of a psychological approach in some individuals to integrate pharmacological treatment is the purpose of review. There is evidence that in some asthmatic patients, the excessive use of social networks can induce depression and stress triggering bronchial obstruction, whereas in others their rational use can induce beneficial effects in terms of asthma management. The increasing asthma prevalence in developed countries seen at the end of last century has raised concern for the considerable burden of this disease on society as well as individuals. Bronchial asthma is a disease in which psychological implications play a role in increasing or in reducing the severity of bronchial obstruction. Internet and, in particular, social media are increasingly a part of daily life of both young and adult people, thus allowing virtual relationships with peers sharing similar interests and goals. Although social network users often disclose more about themselves online than they do in person, there might be a risk for adolescents and for sensitive individuals, who can be negatively influenced by an incorrect use. However, although some studies show an increased risk of depression, other observations suggest beneficial effects of social networks by enhancing communication, social connection and self-esteem.

PERSONAL MARKETING OF DOCTORS IN THE CONTEXT OF SOCIAL NETWORKS

Directory of Open Access Journals (Sweden)

Corina Anamaria IOAN

2014-12-01

Full Text Available More than ever doctors are beginning to recognize that beyond impeccable professionalism shown to the patient, equally imports became part of communication, and in one century of the Internet, the most effective communication process moves online, in the social networks. It is important for doctors to develop a personal brand because a reputation, passed with internet speed can only have a positive effect. In a century in which patients make the decision to see a particular doctor, largely based on recommendations and research the forums online discussions, doctors are beginning realize the importance of a strong presence, constant and reliable environment through online networks social priority.

Mining social networks and security informatics

CERN Document Server

Özyer, Tansel; Rokne, Jon; Khoury, Suheil

2013-01-01

Crime, terrorism and security are in the forefront of current societal concerns. This edited volume presents research based on social network techniques showing how data from crime and terror networks can be analyzed and how information can be extracted. The topics covered include crime data mining and visualization; organized crime detection; crime network visualization; computational criminology; aspects of terror network analyses and threat prediction including cyberterrorism and the related area of dark web; privacy issues in social networks; security informatics; graph algorithms for soci

A Social Networks in Education

Science.gov (United States)

Klimova, Blanka; Poulova, Petra

2015-01-01

At present social networks are becoming important in all areas of human activities. They are simply part and parcel of everyday life. They are mostly used for advertising, but they have already found their way into education. The future potential of social networks is high as it can be seen from their statistics on a daily, monthly or yearly…

Social Networking Goes to School

Science.gov (United States)

Davis, Michelle R.

2010-01-01

Just a few years ago, social networking meant little more to educators than the headache of determining whether to penalize students for inappropriate activities captured on Facebook or MySpace. Now, teachers and students have an array of social-networking sites and tools--from Ning to VoiceThread and Second Life--to draw on for such serious uses…

The anatomy of urban social networks and its implications in the searchability problem

Science.gov (United States)

Herrera-Yagüe, C.; Schneider, C. M.; Couronné, T.; Smoreda, Z.; Benito, R. M.; Zufiria, P. J.; González, M. C.

2015-01-01

The appearance of large geolocated communication datasets has recently increased our understanding of how social networks relate to their physical space. However, many recurrently reported properties, such as the spatial clustering of network communities, have not yet been systematically tested at different scales. In this work we analyze the social network structure of over 25 million phone users from three countries at three different scales: country, provinces and cities. We consistently find that this last urban scenario presents significant differences to common knowledge about social networks. First, the emergence of a giant component in the network seems to be controlled by whether or not the network spans over the entire urban border, almost independently of the population or geographic extension of the city. Second, urban communities are much less geographically clustered than expected. These two findings shed new light on the widely-studied searchability in self-organized networks. By exhaustive simulation of decentralized search strategies we conclude that urban networks are searchable not through geographical proximity as their country-wide counterparts, but through an homophily-driven community structure. PMID:26035529

Querying Large Biological Network Datasets

Science.gov (United States)

Gulsoy, Gunhan

2013-01-01

New experimental methods has resulted in increasing amount of genetic interaction data to be generated every day. Biological networks are used to store genetic interaction data gathered. Increasing amount of data available requires fast large scale analysis methods. Therefore, we address the problem of querying large biological network datasets.…

Urbanism, Neighborhood Context, and Social Networks.

Science.gov (United States)

Cornwell, Erin York; Behler, Rachel L

2015-09-01

Theories of urbanism suggest that the urban context erodes individuals' strong social ties with friends and family. Recent research has narrowed focus to the neighborhood context, emphasizing how localized structural disadvantage affects community-level cohesion and social capital. In this paper, we argue that neighborhood context also shapes social ties with friends and family- particularly for community-dwelling seniors. We hypothesize that neighborhood disadvantage, residential instability, and disorder restrict residents' abilities to cultivate close relationships with neighbors and non-neighbor friends and family. Using data from the National Social Life, Health, and Aging Project (NSHAP), we find that older adults who live in disadvantaged neighborhoods have smaller social networks. Neighborhood disadvantage is also associated with less close network ties and less frequent interaction - but only among men. Furthermore, residents of disordered neighborhoods have smaller networks and weaker ties. We urge scholars to pay greater attention to how neighborhood context contributes to disparities in network-based access to resources.

[Social networks in drinking behaviors among Japanese: support network, drinking network, and intervening network].

Science.gov (United States)

Yoshihara, Chika; Shimizu, Shinji

2005-10-01

The national representative sample was analyzed to examine the relationship between respondents' drinking practice and the social network which was constructed of three different types of network: support network, drinking network, and intervening network. Non-parametric statistical analysis was conducted with chi square method and ANOVA analysis, due to the risk of small samples in some basic tabulation cells. The main results are as follows: (1) In the support network of workplace associates, moderate drinkers enjoyed much more sociable support care than both nondrinkers and hard drinkers, which might suggest a similar effect as the French paradox. Meanwhile in the familial and kinship network, the more intervening care support was provided, the harder respondents' drinking practice. (2) The drinking network among Japanese people for both sexes is likely to be convergent upon certain types of network categories and not decentralized in various categories. This might reflect of the drinking culture of Japan, which permits people to drink everyday as a practice, especially male drinkers. Subsequently, solitary drinking is not optional for female drinkers. (3) Intervening network analysis showed that the harder the respondents' drinking practices, the more frequently their drinking behaviors were checked in almost all the categories of network. A rather complicated gender double-standard was found in the network of hard drinkers with their friends, particularly for female drinkers. Medical professionals played a similar intervening role for men as family and kinship networks but to a less degree than friends for females. The social network is considerably associated with respondents' drinking, providing both sociability for moderate drinkers and intervention for hard drinkers, depending on network categories. To minimize the risk of hard drinking and advance self-healthy drinking there should be more research development on drinking practice and the social network.

Mining of the social network extraction

Science.gov (United States)

Nasution, M. K. M.; Hardi, M.; Syah, R.

2017-01-01

The use of Web as social media is steadily gaining ground in the study of social actor behaviour. However, information in Web can be interpreted in accordance with the ability of the method such as superficial methods for extracting social networks. Each method however has features and drawbacks: it cannot reveal the behaviour of social actors, but it has the hidden information about them. Therefore, this paper aims to reveal such information in the social networks mining. Social behaviour could be expressed through a set of words extracted from the list of snippets.

Unraveling the disease consequences and mechanisms of modular structure in animal social networks

Science.gov (United States)

Sah, Pratha; Leu, Stephan T.; Cross, Paul C.; Hudson, Peter J.; Bansal, Shweta

2017-01-01

Disease risk is a potential cost of group living. Although modular organization is thought to reduce this cost in animal societies, empirical evidence toward this hypothesis has been conflicting. We analyzed empirical social networks from 43 animal species to motivate our study of the epidemiological consequences of modular structure in animal societies. From these empirical studies, we identified the features of interaction patterns associated with network modularity and developed a theoretical network model to investigate when and how subdivisions in social networks influence disease dynamics. Contrary to prior work, we found that disease risk is largely unaffected by modular structure, although social networks beyond a modular threshold experience smaller disease burden and longer disease duration. Our results illustrate that the lowering of disease burden in highly modular social networks is driven by two mechanisms of modular organization: network fragmentation and subgroup cohesion. Highly fragmented social networks with cohesive subgroups are able to structurally trap infections within a few subgroups and also cause a structural delay to the spread of disease outbreaks. Finally, we show that network models incorporating modular structure are necessary only when prior knowledge suggests that interactions within the population are highly subdivided. Otherwise, null networks based on basic knowledge about group size and local contact heterogeneity may be sufficient when data-limited estimates of epidemic consequences are necessary. Overall, our work does not support the hypothesis that modular structure universally mitigates the disease impact of group living.

Real-time community detection in full social networks on a laptop

Science.gov (United States)

Chamberlain, Benjamin Paul; Levy-Kramer, Josh; Humby, Clive

2018-01-01

For a broad range of research and practical applications it is important to understand the allegiances, communities and structure of key players in society. One promising direction towards extracting this information is to exploit the rich relational data in digital social networks (the social graph). As global social networks (e.g., Facebook and Twitter) are very large, most approaches make use of distributed computing systems for this purpose. Distributing graph processing requires solving many difficult engineering problems, which has lead some researchers to look at single-machine solutions that are faster and easier to maintain. In this article, we present an approach for analyzing full social networks on a standard laptop, allowing for interactive exploration of the communities in the locality of a set of user specified query vertices. The key idea is that the aggregate actions of large numbers of users can be compressed into a data structure that encapsulates the edge weights between vertices in a derived graph. Local communities can be constructed by selecting vertices that are connected to the query vertices with high edge weights in the derived graph. This compression is robust to noise and allows for interactive queries of local communities in real-time, which we define to be less than the average human reaction time of 0.25s. We achieve single-machine real-time performance by compressing the neighborhood of each vertex using minhash signatures and facilitate rapid queries through Locality Sensitive Hashing. These techniques reduce query times from hours using industrial desktop machines operating on the full graph to milliseconds on standard laptops. Our method allows exploration of strongly associated regions (i.e., communities) of large graphs in real-time on a laptop. It has been deployed in software that is actively used by social network analysts and offers another channel for media owners to monetize their data, helping them to continue to provide

Real-time community detection in full social networks on a laptop.

Directory of Open Access Journals (Sweden)

Benjamin Paul Chamberlain

Full Text Available For a broad range of research and practical applications it is important to understand the allegiances, communities and structure of key players in society. One promising direction towards extracting this information is to exploit the rich relational data in digital social networks (the social graph. As global social networks (e.g., Facebook and Twitter are very large, most approaches make use of distributed computing systems for this purpose. Distributing graph processing requires solving many difficult engineering problems, which has lead some researchers to look at single-machine solutions that are faster and easier to maintain. In this article, we present an approach for analyzing full social networks on a standard laptop, allowing for interactive exploration of the communities in the locality of a set of user specified query vertices. The key idea is that the aggregate actions of large numbers of users can be compressed into a data structure that encapsulates the edge weights between vertices in a derived graph. Local communities can be constructed by selecting vertices that are connected to the query vertices with high edge weights in the derived graph. This compression is robust to noise and allows for interactive queries of local communities in real-time, which we define to be less than the average human reaction time of 0.25s. We achieve single-machine real-time performance by compressing the neighborhood of each vertex using minhash signatures and facilitate rapid queries through Locality Sensitive Hashing. These techniques reduce query times from hours using industrial desktop machines operating on the full graph to milliseconds on standard laptops. Our method allows exploration of strongly associated regions (i.e., communities of large graphs in real-time on a laptop. It has been deployed in software that is actively used by social network analysts and offers another channel for media owners to monetize their data, helping them to

Real-time community detection in full social networks on a laptop.

Science.gov (United States)

Chamberlain, Benjamin Paul; Levy-Kramer, Josh; Humby, Clive; Deisenroth, Marc Peter

2018-01-01

For a broad range of research and practical applications it is important to understand the allegiances, communities and structure of key players in society. One promising direction towards extracting this information is to exploit the rich relational data in digital social networks (the social graph). As global social networks (e.g., Facebook and Twitter) are very large, most approaches make use of distributed computing systems for this purpose. Distributing graph processing requires solving many difficult engineering problems, which has lead some researchers to look at single-machine solutions that are faster and easier to maintain. In this article, we present an approach for analyzing full social networks on a standard laptop, allowing for interactive exploration of the communities in the locality of a set of user specified query vertices. The key idea is that the aggregate actions of large numbers of users can be compressed into a data structure that encapsulates the edge weights between vertices in a derived graph. Local communities can be constructed by selecting vertices that are connected to the query vertices with high edge weights in the derived graph. This compression is robust to noise and allows for interactive queries of local communities in real-time, which we define to be less than the average human reaction time of 0.25s. We achieve single-machine real-time performance by compressing the neighborhood of each vertex using minhash signatures and facilitate rapid queries through Locality Sensitive Hashing. These techniques reduce query times from hours using industrial desktop machines operating on the full graph to milliseconds on standard laptops. Our method allows exploration of strongly associated regions (i.e., communities) of large graphs in real-time on a laptop. It has been deployed in software that is actively used by social network analysts and offers another channel for media owners to monetize their data, helping them to continue to provide

SocialBrowsing: Integrating Social Networks and Web Browsing

National Research Council Canada - National Science Library

Golbeck, Jennifer; Wasser, Michael M

2007-01-01

.... The extension is paired with services provided by social networking websites, analyzes the page's contents, and adds tooltips and highlighting to indicate when there is relevant social information...

Adolescent Problematic Social Networking and School Experiences: The Mediating Effects of Sleep Disruptions and Sleep Quality.

Science.gov (United States)

Vernon, Lynette; Barber, Bonnie L; Modecki, Kathryn L

2015-07-01

An important developmental task for adolescents is to become increasingly responsible for their own health behaviors. Establishing healthy sleep routines and controlling media use before bedtime are important for adequate, quality sleep so adolescents are alert during the day and perform well at school. Despite the prevalence of adolescent social media use and the large percentage of computers and cell phones in adolescents' bedrooms, no studies to date have investigated the link between problematic adolescent investment in social networking, their sleep practices, and associated experiences at school. A sample of 1,886 students in Australia aged between 12 and 18 years of age completed self-report data on problematic social networking use, sleep disturbances, sleep quality, and school satisfaction. Structural equation modeling (SEM) substantiated the serial mediation hypothesis: for adolescents, problematic social networking use significantly increased sleep disturbances, which adversely affected perceptions of sleep quality that, in turn, lowered adolescents' appraisals of their school satisfaction. This significant pattern was largely driven by the indirect effect of sleep disturbances. These findings suggest that adolescents are vulnerable to negative consequences from social networking use. Specifically, problematic social networking is associated with poor school experiences, which result from poor sleep habits. Promoting better sleep routines by minimizing sleep disturbances from social media use could improve school experiences for adolescents with enhanced emotional engagement and improved subjective well-being.

Social Software: Participants' Experience Using Social Networking for Learning

Science.gov (United States)

Batchelder, Cecil W.

2010-01-01

Social networking tools used in learning provides instructional design with tools for transformative change in education. This study focused on defining the meanings and essences of social networking through the lived common experiences of 7 college students. The problem of the study was a lack of learner voice in understanding the value of social…

EXPLORING THE ROLE OF BUSINESS SOCIAL NETWORKING FOR ORGANIZATIONS

Directory of Open Access Journals (Sweden)

Damjana Jerman

2015-01-01

Full Text Available This article explores the relationship between communication, with the emphasis on public relations, and social network perspectives. What, then, does social networking for business mean in communication, particularly in public relations? This paper argues that business social networking play an important role in improving organizations communications. The goal of our paper is to identify the basic characteristics of social networks and its role for public relations for the effective implementation of social networking initiatives and tools in the workplace. Business social networking tools such as Facebook and LinkedIn are being used by organizations to reach the corporate objectives and to create a positive company image. Specific social networks, such the personalised networks of influence, are perceived to be one of the main strategic resources for organizations.

Social power and opinion formation in complex networks

Science.gov (United States)

Jalili, Mahdi

2013-02-01

In this paper we investigate the effects of social power on the evolution of opinions in model networks as well as in a number of real social networks. A continuous opinion formation model is considered and the analysis is performed through numerical simulation. Social power is given to a proportion of agents selected either randomly or based on their degrees. As artificial network structures, we consider scale-free networks constructed through preferential attachment and Watts-Strogatz networks. Numerical simulations show that scale-free networks with degree-based social power on the hub nodes have an optimal case where the largest number of the nodes reaches a consensus. However, given power to a random selection of nodes could not improve consensus properties. Introducing social power in Watts-Strogatz networks could not significantly change the consensus profile.

Internet gaming disorder, social network disorder and laterality: handedness relates to pathological use of social networks.

Science.gov (United States)

Bouna-Pyrrou, Polyxeni; Mühle, Christiane; Kornhuber, Johannes; Lenz, Bernd

2015-08-01

The internet age bears new challenges that include health risks. It is agreed that excessive internet use may reach pathological levels. However, the concept of internet addiction lacks specificity and, therefore, warrants studies on its diagnostic and etiologic classification. This study was conducted to characterize the novel DSM-5 criteria for internet gaming disorder and the adapted criteria for the "social network disorder". Based on the established association of handedness and substance use disorders, we also explored whether internet use related to laterality. For this study, 3,287 volunteers participated in the online survey and gave particulars concerning their internet use in general, internet gaming and use of social networks, laterality markers (hand, foot, eye, ear, rotational preference in gymnastics, and head turning asymmetry) and health status. Of the participants, 1.1 % fulfilled the criteria for internet gaming disorder, and 1.8 % fulfilled the criteria for social network disorder. The applied criteria were highly correlated with the time spent on the respective internet activities (p social networks (p ≤ 4 × 10(-2)). The provided criteria proved to be user-friendly, comprehensible and well accepted. The results contribute to a better understanding of pathological internet gaming and social network use and provide evidence that biological markers of substance use disorders are involved in internet addiction.

Fast katz and commuters : efficient estimation of social relatedness in large networks.

Energy Technology Data Exchange (ETDEWEB)

On, Byung-Won (University of British Columbia, Vancouver BC, Canada); Lakshmanan, Laks V. S. (University of British Columbia, Vancouver BC, Canada); Greif, Chen (University of British Columbia, Vancouver BC, Canada); Esfandiar, Pooya (University of British Columbia, Vancouver BC, Canada); Bonchi, Francesco (Yahoo! Research, Barcelona, Spain); Gleich, David F.

2010-09-01

Motivated by social network data mining problems such as link prediction and collaborative filtering, significant research effort has been devoted to computing topological measures including the Katz score and the commute time. Existing approaches typically approximate all pairwise relationships simultaneously. In this paper, we are interested in computing: the score for a single pair of nodes, and the top-k nodes with the best scores from a given source node. For the pairwise problem, we apply an iterative algorithm that computes upper and lower bounds for the measures we seek. This algorithm exploits a relationship between the Lanczos process and a quadrature rule. For the top-k problem, we propose an algorithm that only accesses a small portion of the graph and is related to techniques used in personalized PageRank computing. To test the scalability and accuracy of our algorithms we experiment with three real-world networks and find that these algorithms run in milliseconds to seconds without any preprocessing.

"I Don't Know What Fun Is": Examining the Intersection of Social Capital, Social Networks, and Social Recovery.

Science.gov (United States)

Boeri, Miriam; Gardner, Megan; Gerken, Erin; Ross, Melissa; Wheeler, Jack

The purpose of this paper is to understand how people with problematic drug use access positive social capital. Social capital is defined as relations that provide valuable resources to individuals through participation in social networks. People with low socioeconomic status remain at a disadvantage for acquiring positive social capital, a component of recovery capital. The concept of social recovery emphasises the relational processes of recovery. In-depth life history data were collected from 29 individuals who used heroin, cocaine, crack, or methamphetamine for at least five years, have less than a high school education, and unstable employment and housing. Qualitative data were coded for social networks accessed throughout the life course, distinguished by bonding, bridging and linking social capital. Social networks included drug treatment programs; non-drug-using family and friends; religious/spiritual groups; workplace networks, and social clubs/activities. Bonding and/or bridging social capital were acquired through treatment, family and friends, religious/spiritual groups, workplaces, and social clubs. Linking social capital was not acquired through any social networks available, and many barriers to accessing mainstream social networks were found. This is a small study conducted in the US. A greater focus on social recovery is needed to achieve sustained recovery for individuals lacking access to and engagement in mainstream social networks. Social recovery is proposed as an analytical tool as well as for developing prevention, intervention, and treatment strategies.

The interplay between social networks and culture: theoretically and among whales and dolphins.

Science.gov (United States)

Cantor, Mauricio; Whitehead, Hal

2013-05-19

Culture is increasingly being understood as a driver of mammalian phenotypes. Defined as group-specific behaviour transmitted by social learning, culture is shaped by social structure. However, culture can itself affect social structure if individuals preferentially interact with others whose behaviour is similar, or cultural symbols are used to mark groups. Using network formalism, this interplay can be depicted by the coevolution of nodes and edges together with the coevolution of network topology and transmission patterns. We review attempts to model the links between the spread, persistence and diversity of culture and the network topology of non-human societies. We illustrate these processes using cetaceans. The spread of socially learned begging behaviour within a population of bottlenose dolphins followed the topology of the social network, as did the evolution of the song of the humpback whale between breeding areas. In three bottlenose dolphin populations, individuals preferentially associated with animals using the same socially learned foraging behaviour. Homogeneous behaviour within the tight, nearly permanent social structures of the large matrilineal whales seems to result from transmission bias, with cultural symbols marking social structures. We recommend the integration of studies of culture and society in species for which social learning is an important determinant of behaviour.

Social networks of patients with psychosis: a systematic review.

Science.gov (United States)

Palumbo, Claudia; Volpe, Umberto; Matanov, Aleksandra; Priebe, Stefan; Giacco, Domenico

2015-10-12

Social networks are important for mental health outcomes as they can mobilise resources and help individuals to cope with social stressors. Individuals with psychosis may have specific difficulties in establishing and maintaining social relationships which impacts on their well-being and quality of life. There has been a growing interest in developing social network interventions for patients with psychotic disorders. A systematic literature review was conducted to investigate the size of social networks of patients with psychotic disorders, as well as their friendship networks. A systematic electronic search was carried out in MEDLINE, EMBASE and PsychINFO databases using a combination of search terms relating to 'social network', 'friendship' and 'psychotic disorder'. The search identified 23 relevant papers. Out of them, 20 reported patient social network size. Four papers reported the mean number of friends in addition to whole network size, while three further papers focused exclusively on the number of friends. Findings varied substantially across the studies, with a weighted mean size of 11.7 individuals for whole social networks and 3.4 individuals for friendship networks. On average, 43.1 % of the whole social network was composed of family members, while friends accounted for 26.5 %. Studies assessing whole social network size and friendship networks of people with psychosis are difficult to compare as different concepts and methods of assessment were applied. The extent of the overlap between different social roles assessed in the networks was not always clear. Greater conceptual and methodological clarity is needed in order to help the development of effective strategies to increase social resources of patients with psychosis.

Social Networking Sites and Addiction: Ten Lessons Learned.

Science.gov (United States)

Kuss, Daria J; Griffiths, Mark D

2017-03-17

Online social networking sites (SNSs) have gained increasing popularity in the last decade, with individuals engaging in SNSs to connect with others who share similar interests. The perceived need to be online may result in compulsive use of SNSs, which in extreme cases may result in symptoms and consequences traditionally associated with substance-related addictions. In order to present new insights into online social networking and addiction, in this paper, 10 lessons learned concerning online social networking sites and addiction based on the insights derived from recent empirical research will be presented. These are: (i) social networking and social media use are not the same; (ii) social networking is eclectic; (iii) social networking is a way of being; (iv) individuals can become addicted to using social networking sites; (v) Facebook addiction is only one example of SNS addiction; (vi) fear of missing out (FOMO) may be part of SNS addiction; (vii) smartphone addiction may be part of SNS addiction; (viii) nomophobia may be part of SNS addiction; (ix) there are sociodemographic differences in SNS addiction; and (x) there are methodological problems with research to date. These are discussed in turn. Recommendations for research and clinical applications are provided.

Composite Social Network for Predicting Mobile Apps Installation

Science.gov (United States)

2011-06-02

Social network tools (such as the Facebook app and the Twitter app) can observe users’ online friendship network . In this work, our key idea is...the friendship network from phones by collecting data from social networking apps such as the Facebook and Twitter apps. We summarize all the networks ...ar X iv :1 10 6. 03 59 v1 [ cs .S I] 2 J un 2 01 1 Composite Social Network for Predicting Mobile Apps Installation Wei Pan

How can social network analysis contribute to social behavior research in applied ethology?

Science.gov (United States)

Makagon, Maja M; McCowan, Brenda; Mench, Joy A

2012-05-01

Social network analysis is increasingly used by behavioral ecologists and primatologists to describe the patterns and quality of interactions among individuals. We provide an overview of this methodology, with examples illustrating how it can be used to study social behavior in applied contexts. Like most kinds of social interaction analyses, social network analysis provides information about direct relationships (e.g. dominant-subordinate relationships). However, it also generates a more global model of social organization that determines how individual patterns of social interaction relate to individual and group characteristics. A particular strength of this approach is that it provides standardized mathematical methods for calculating metrics of sociality across levels of social organization, from the population and group levels to the individual level. At the group level these metrics can be used to track changes in social network structures over time, evaluate the effect of the environment on social network structure, or compare social structures across groups, populations or species. At the individual level, the metrics allow quantification of the heterogeneity of social experience within groups and identification of individuals who may play especially important roles in maintaining social stability or information flow throughout the network.

Growth Limits in Large Scale Networks

DEFF Research Database (Denmark)

Knudsen, Thomas Phillip

limitations. The rising complexity of network management with the convergence of communications platforms is shown as problematic for both automatic management feasibility and for manpower resource management. In the fourth step the scope is extended to include the present society with the DDN project as its......The Subject of large scale networks is approached from the perspective of the network planner. An analysis of the long term planning problems is presented with the main focus on the changing requirements for large scale networks and the potential problems in meeting these requirements. The problems...... the fundamental technological resources in network technologies are analysed for scalability. Here several technological limits to continued growth are presented. The third step involves a survey of major problems in managing large scale networks given the growth of user requirements and the technological...

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.

The structural and functional brain networks that support human social networks.

Science.gov (United States)

Noonan, M P; Mars, R B; Sallet, J; Dunbar, R I M; Fellows, L K

2018-02-20

Social skills rely on a specific set of cognitive processes, raising the possibility that individual differences in social networks are related to differences in specific brain structural and functional networks. Here, we tested this hypothesis with multimodality neuroimaging. With diffusion MRI (DMRI), we showed that differences in structural integrity of particular white matter (WM) tracts, including cingulum bundle, extreme capsule and arcuate fasciculus were associated with an individual's social network size (SNS). A voxel-based morphology analysis demonstrated correlations between gray matter (GM) volume and SNS in limbic and temporal lobe regions. These structural changes co-occured with functional network differences. As a function of SNS, dorsomedial and dorsolateral prefrontal cortex showed altered resting-state functional connectivity with the default mode network (DMN). Finally, we integrated these three complementary methods, interrogating the relationship between social GM clusters and specific WM and resting-state networks (RSNs). Probabilistic tractography seeded in these GM nodes utilized the SNS-related WM pathways. Further, the spatial and functional overlap between the social GM clusters and the DMN was significantly closer than other control RSNs. These integrative analyses provide convergent evidence of the role of specific circuits in SNS, likely supporting the adaptive behavior necessary for success in extensive social environments. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

Social Network Sites, Individual Social Capital and Happiness

NARCIS (Netherlands)

E. Arampatzi (Efstratia); M.J. Burger (Martijn); N.A. Novik (Natallia)

2016-01-01

textabstractCan online social contacts replace the importance of real-life social connections in our pursuit of happiness? With the growing use of social network sites (SNSs), attention has been increasingly drawn to this topic. Our study empirically examines the effect of SNS use on happiness for

Social networking and privacy attitudes among

OpenAIRE

Kristen A. Carruth; Harvey J. Ginsburg

2014-01-01

Daily use of social networking sites (SNS) such as Facebook has become routine for millions of Internet users. Facebook is currently still the most popular social media site. Social networking has been rapidly adopted by societies around the world. In particular, social media like Facebook provide sites where users can personalize a profile with their information, pictures, and videos that can be shared with other users. This information can be used in ways that may violate users’ privacy ...

A Social Network Analysis of Occupational Segregation

DEFF Research Database (Denmark)

Buhai, Ioan Sebastian; van der Leij, Marco

We develop a social network model of occupational segregation between different social groups, generated by the existence of positive inbreeding bias among individuals from the same group. If network referrals are important for job search, then expected homophily in the contact network structure...

Characterizing Social Interaction in Tobacco-Oriented Social Networks: An Empirical Analysis.

Science.gov (United States)

Liang, Yunji; Zheng, Xiaolong; Zeng, Daniel Dajun; Zhou, Xingshe; Leischow, Scott James; Chung, Wingyan

2015-06-19

Social media is becoming a new battlefield for tobacco "wars". Evaluating the current situation is very crucial for the advocacy of tobacco control in the age of social media. To reveal the impact of tobacco-related user-generated content, this paper characterizes user interaction and social influence utilizing social network analysis and information theoretic approaches. Our empirical studies demonstrate that the exploding pro-tobacco content has long-lasting effects with more active users and broader influence, and reveal the shortage of social media resources in global tobacco control. It is found that the user interaction in the pro-tobacco group is more active, and user-generated content for tobacco promotion is more successful in obtaining user attention. Furthermore, we construct three tobacco-related social networks and investigate the topological patterns of these tobacco-related social networks. We find that the size of the pro-tobacco network overwhelms the others, which suggests a huge number of users are exposed to the pro-tobacco content. These results indicate that the gap between tobacco promotion and tobacco control is widening and tobacco control may be losing ground to tobacco promotion in social media.

Modelling of information diffusion on social networks with applications to WeChat

Science.gov (United States)

Liu, Liang; Qu, Bo; Chen, Bin; Hanjalic, Alan; Wang, Huijuan

2018-04-01

Traces of user activities recorded in online social networks open new possibilities to systematically understand the information diffusion process on social networks. From the online social network WeChat, we collected a large number of information cascade trees, each of which tells the spreading trajectory of a message/information such as which user creates the information and which users view or forward the information shared by which neighbours. In this work, we propose two heterogeneous non-linear models, one for the topologies of the information cascade trees and the other for the stochastic process of information diffusion on a social network. Both models are validated by the WeChat data in reproducing and explaining key features of cascade trees. Specifically, we apply the Random Recursive Tree (RRT) to model the growth of cascade trees. The RRT model could capture key features, i.e. the average path length and degree variance of a cascade tree in relation to the number of nodes (size) of the tree. Its single identified parameter quantifies the relative depth or broadness of the cascade trees and indicates that information propagates via a star-like broadcasting or viral-like hop by hop spreading. The RRT model explains the appearance of hubs, thus a possibly smaller average path length as the cascade size increases, as observed in WeChat. We further propose the stochastic Susceptible View Forward Removed (SVFR) model to depict the dynamic user behaviour including creating, viewing, forwarding and ignoring a message on a given social network. Beside the average path length and degree variance of the cascade trees in relation to their sizes, the SVFR model could further explain the power-law cascade size distribution in WeChat and unravel that a user with a large number of friends may actually have a smaller probability to read a message (s)he receives due to limited attention.

SOCIAL NETWORKS BETWEEN ICTS AND MORAL DECADENCE

Directory of Open Access Journals (Sweden)

Domingo Alarcón Ortiz

2013-07-01

Full Text Available The paradox of social networks in organizations is that they are a very important means of formation, training, update, information and communication, but also represent a symptom of cultural decay, because with them have been provided and processes of disinformation uncontrolled distribution of malicious information, which is assaulted by people. The abuse as to upload information indiscriminately leads to pathological, anti-social and cynical time’s behaviors. As many users of social networks does not assume a code of ethics according to social needs, then its limits of performance in terms of dignity and self-respect will not operate, constitute a serious social threat, against which the appropriate response has not been generated.  To participate in social networks, people end up exposing itself to that your privacy was hurt with impunity and thereby will limit or annul the opportunity to defend their dignity, turning them into a set of highly vulnerable entities. But as there is social by joining the network pressure, the question is it worth being in these networks? If you want to stay informed and share information, raises the dilemma of to where it can and should go.

Stories in Networks and Networks in Stories: A Tri-Modal Model for Mixed-Methods Social Network Research on Teachers

Science.gov (United States)

Baker-Doyle, Kira J.

2015-01-01

Social network research on teachers and schools has risen exponentially in recent years as an innovative method to reveal the role of social networks in education. However, scholars are still exploring ways to incorporate traditional quantitative methods of Social Network Analysis (SNA) with qualitative approaches to social network research. This…

Connecting Social Networks with Ecosystem Services for Watershed Governance: a Social-Ecological Network Perspective Highlights the Critical Role of Bridging Organizations

Directory of Open Access Journals (Sweden)

Kaitlyn J. Rathwell

2012-06-01

Full Text Available In many densely settled agricultural watersheds, water quality is a point of conflict between amenity and agricultural activities because of the varied demands and impacts on shared water resources. Successful governance of these watersheds requires coordination among different activities. Recent research has highlighted the role that social networks between management entities can play to facilitate cross-scale interaction in watershed governance. For example, bridging organizations can be positioned in social networks to bridge local initiatives done by single municipalities across whole watersheds. To better understand the role of social networks in social-ecological system dynamics, we combine a social network analysis of the water quality management networks held by local governments with a social-ecological analysis of variation in water management and ecosystem services across the Montérégie, an agricultural landscape near Montréal, Québec, Canada. We analyze municipal water management networks by using one-mode networks to represent direct collaboration between municipalities, and two-mode networks to capture how bridging organizations indirectly connect municipalities. We find that municipalities do not collaborate directly with one another but instead are connected via bridging organizations that span the water quality management network. We also discovered that more connected municipalities engaged in more water management activities. However, bridging organizations preferentially connected with municipalities that used more tourism related ecosystem services rather than those that used more agricultural ecosystem services. Many agricultural municipalities were relatively isolated, despite being the main producers of water quality problems. In combination, these findings suggest that further strengthening the water management network in the Montérégie will contribute to improving water quality in the region. However, such