WorldWideScience

Sample records for modeling social network

  1. Assortative model for social networks

    Science.gov (United States)

    Catanzaro, Michele; Caldarelli, Guido; Pietronero, Luciano

    2004-09-01

    In this Brief Report we present a version of a network growth model, generalized in order to describe the behavior of social networks. The case of study considered is the preprint archive at cul.arxiv.org. Each node corresponds to a scientist, and a link is present whenever two authors wrote a paper together. This graph is a nice example of degree-assortative network, that is, to say a network where sites with similar degree are connected to each other. The model presented is one of the few able to reproduce such behavior, giving some insight on the microscopic dynamics at the basis of the graph structure.

  2. 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.

  3. 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

  4. An evolutionary model of social networks

    Science.gov (United States)

    Ludwig, M.; Abell, P.

    2007-07-01

    Social networks in communities, markets, and societies self-organise through the interactions of many individuals. In this paper we use a well-known mechanism of social interactions — the balance of sentiment in triadic relations — to describe the development of social networks. Our model contrasts with many existing network models, in that people not only establish but also break up relations whilst the network evolves. The procedure generates several interesting network features such as a variety of degree distributions and degree correlations. The resulting network converges under certain conditions to a steady critical state where temporal disruptions in triangles follow a power-law distribution.

  5. Topological evolution of virtual social networks by modeling social activities

    Science.gov (United States)

    Sun, Xin; Dong, Junyu; Tang, Ruichun; Xu, Mantao; Qi, Lin; Cai, Yang

    2015-09-01

    With the development of Internet and wireless communication, virtual social networks are becoming increasingly important in the formation of nowadays' social communities. Topological evolution model is foundational and critical for social network related researches. Up to present most of the related research experiments are carried out on artificial networks, however, a study of incorporating the actual social activities into the network topology model is ignored. This paper first formalizes two mathematical abstract concepts of hobbies search and friend recommendation to model the social actions people exhibit. Then a social activities based topology evolution simulation model is developed to satisfy some well-known properties that have been discovered in real-world social networks. Empirical results show that the proposed topology evolution model has embraced several key network topological properties of concern, which can be envisioned as signatures of real social networks.

  6. Object Oriented Modeling Of Social Networks

    NARCIS (Netherlands)

    Zeggelink, Evelien P.H.; Oosten, Reinier van; Stokman, Frans N.

    1996-01-01

    The aim of this paper is to explain principles of object oriented modeling in the scope of modeling dynamic social networks. As such, the approach of object oriented modeling is advocated within the field of organizational research that focuses on networks. We provide a brief introduction into the f

  7. Gossip spread in social network Models

    Science.gov (United States)

    Johansson, Tobias

    2017-04-01

    Gossip almost inevitably arises in real social networks. In this article we investigate the relationship between the number of friends of a person and limits on how far gossip about that person can spread in the network. How far gossip travels in a network depends on two sets of factors: (a) factors determining gossip transmission from one person to the next and (b) factors determining network topology. For a simple model where gossip is spread among people who know the victim it is known that a standard scale-free network model produces a non-monotonic relationship between number of friends and expected relative spread of gossip, a pattern that is also observed in real networks (Lind et al., 2007). Here, we study gossip spread in two social network models (Toivonen et al., 2006; Vázquez, 2003) by exploring the parameter space of both models and fitting them to a real Facebook data set. Both models can produce the non-monotonic relationship of real networks more accurately than a standard scale-free model while also exhibiting more realistic variability in gossip spread. Of the two models, the one given in Vázquez (2003) best captures both the expected values and variability of gossip spread.

  8. Modelling Users` Trust in Online Social Networks

    Directory of Open Access Journals (Sweden)

    Iacob Cătoiu

    2014-02-01

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

  9. Multiple Social Networks, Data Models and Measures for

    DEFF Research Database (Denmark)

    Magnani, Matteo; Rossi, Luca

    2017-01-01

    Multiple Social Network Analysis is a discipline defining models, measures, methodologies, and algorithms to study multiple social networks together as a single social system. It is particularly valuable when the networks are interconnected, e.g., the same actors are present in more than one...... network....

  10. A Model of Genetic Variation in Human Social Networks

    CERN Document Server

    Fowler, James H; Christakis, Nicholas A

    2008-01-01

    Social networks influence the evolution of cooperation and they exhibit strikingly systematic patterns across a wide range of human contexts. Both of these facts suggest that variation in the topological attributes of human social networks might have a genetic basis. While genetic variation accounts for a significant portion of the variation in many complex social behaviors, the heritability of egocentric social network attributes is unknown. Here we show that three of these attributes (in-degree, transitivity, and centrality) are heritable. We then develop a "mirror network" method to test extant network models and show that none accounts for observed genetic variation in human social networks. We propose an alternative "attract and introduce" model that generates significant heritability as well as other important network features, and we show that this model with two simple forms of heterogeneity is well suited to the modeling of real social networks in humans. These results suggest that natural selection ...

  11. Influence Activation Model: A New Perspective in Social Influence Analysis and Social Network Evolution

    CERN Document Server

    Yang, Yang; Lichtenwalter, Ryan N; Dong, Yuxiao

    2016-01-01

    What drives the propensity for the social network dynamics? Social influence is believed to drive both off-line and on-line human behavior, however it has not been considered as a driver of social network evolution. Our analysis suggest that, while the network structure affects the spread of influence in social networks, the network is in turn shaped by social influence activity (i.e., the process of social influence wherein one person's attitudes and behaviors affect another's). To that end, we develop a novel model of network evolution where the dynamics of network follow the mechanism of influence propagation, which are not captured by the existing network evolution models. Our experiments confirm the predictions of our model and demonstrate the important role that social influence can play in the process of network evolution. As well exploring the reason of social network evolution, different genres of social influence have been spotted having different effects on the network dynamics. These findings and ...

  12. Modeling online social networks based on preferential linking

    Institute of Scientific and Technical Information of China (English)

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

    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.

  13. Modeling social influence through network autocorrelation : constructing the weight matrix

    NARCIS (Netherlands)

    Leenders, RTAJ

    2002-01-01

    Many physical and social phenomena are embedded within networks of interdependencies, the so-called 'context' of these phenomena. In network analysis, this type of process is typically modeled as a network autocorrelation model. Parameter estimates and inferences based on autocorrelation models, hin

  14. A last updating evolution model for online social networks

    Science.gov (United States)

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

    2013-05-01

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

  15. Social network models predict movement and connectivity in ecological landscapes

    Science.gov (United States)

    Fletcher, Robert J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, Wiley M.

    2011-01-01

    Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

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

    Science.gov (United States)

    Chung, Kon Shing Kenneth; Paredes, Walter Christian

    2015-01-01

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

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

    Science.gov (United States)

    Chung, Kon Shing Kenneth; Paredes, Walter Christian

    2015-01-01

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

  18. Computational social network modeling of terrorist recruitment.

    Energy Technology Data Exchange (ETDEWEB)

    Berry, Nina M.; Turnley, Jessica Glicken (Sandia National Laboratories, Albuquerque, NM); Smrcka, Julianne D. (Sandia National Laboratories, Albuquerque, NM); Ko, Teresa H.; Moy, Timothy David (Sandia National Laboratories, Albuquerque, NM); Wu, Benjamin C.

    2004-10-01

    The Seldon terrorist model represents a multi-disciplinary approach to developing organization software for the study of terrorist recruitment and group formation. The need to incorporate aspects of social science added a significant contribution to the vision of the resulting Seldon toolkit. The unique addition of and abstract agent category provided a means for capturing social concepts like cliques, mosque, etc. in a manner that represents their social conceptualization and not simply as a physical or economical institution. This paper provides an overview of the Seldon terrorist model developed to study the formation of cliques, which are used as the major recruitment entity for terrorist organizations.

  19. Agent-based model of information spread in social networks

    CERN Document Server

    Lande, D V; Berezin, B O

    2016-01-01

    We propose evolution rules of the multiagent network and determine statistical patterns in life cycle of agents - information messages. The main discussed statistical pattern is connected with the number of likes and reposts for a message. This distribution corresponds to Weibull distribution according to modeling results. We examine proposed model using the data from Twitter, an online social networking service.

  20. Social Network Analyses and Nutritional Behavior: An Integrated Modeling Approach

    Directory of Open Access Journals (Sweden)

    Alistair McNair Senior

    2016-01-01

    Full Text Available Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent advances in nutrition research, combining state-space models of nutritional geometry with agent-based models of systems biology, show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a tangible and practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit agent-based models that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition. Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interaction in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments.

  1. Social Network Analysis and Nutritional Behavior: An Integrated Modeling Approach.

    Science.gov (United States)

    Senior, Alistair M; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J

    2016-01-01

    Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent research combining state-space models of nutritional geometry with agent-based models (ABMs), show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit ABMs that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition). Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interactions in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments.

  2. The multilevel p2 model : A random effects model for the analysis of multiple social networks

    NARCIS (Netherlands)

    Zijlstra, B.J.H.; van Duijn, M.A.J.; Snijders, T.A.B.

    2006-01-01

    The p2 model is a random effects model with covariates for the analysis of binary directed social network data coming from a single observation of a social network. Here, a multilevel variant of the p2 model is proposed for the case of multiple observations of social networks, for example, in a samp

  3. MULTI-FACET TRUST MODEL FOR ONLINE SOCIAL NETWORK ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    Liu Ban Chieng

    2015-01-01

    Full Text Available Online Social Network (OSN has become the most popular platform on the Internet that can provide an interesting and creative ways to communicate, sharing and meets with peoples. As OSNs mature, issues regarding proper use of OSNs are also growing. In this research, the challenges of online social networks have been investigated. The current issues in some of the Social Network Sites are being studied and compared. Cyber criminals, malware attacks, physical threat, security and usability and some privacy issues have been recognized as the challenges of the current social networking sites. Trust concerns have been raised and the trustworthiness of social networking sites has been questioned. Currently, the trust in social networks is using the single- faceted approach, which is not well personalized, and doesn’t account for the subjective views of trust, according to each user, but only the general trust believes of a group of population. The trust level towards a person cannot be calculated and trust is lack of personalization. From our initial survey, we had found that most people can share their information without any doubts on OSN but they normally do not trust all their friends equally and think there is a need of trust management. We had found mixed opinions in relation to the proposed rating feature in OSNs too. By adopting the idea of multi-faceted trust model, a user-centric model that can personalize the comments/photos in social network with user’s customized traits of trust is proposed. This model can probably solve many of the trust issues towards the social networking sites with personalized trust features, in order to keep the postings on social sites confidential and integrity.

  4. A Static Model for Stylized Facts in Social Networks

    CERN Document Server

    Jo, Hang-Hyun; Török, János; Kertész, János; Kaski, Kimmo

    2016-01-01

    The past analyses of available datasets for social networks have given rise to a number of empirical findings that cover only some parts or aspects of the society, but leave the structure of the whole social network largely unexplored due to lack of even more comprehensive datasets. In order to model the whole social network, we assume that some properties of the network are reflected in empirical findings that are commonly featured as \\emph{stylized facts} of social networks, such as broad distributions of network quantities, existence of communities, assortative mixing, and intensity-topology correlations. Several models have been studied to generate the stylized facts, but most of them focus on the processes or mechanisms behind stylized facts. In this paper, we take an alternative approach by devising a static model for the whole social network, for which we randomly assign a number of communities to a given set of isolated nodes using a few assumptions, i.e., the community size is heterogeneous, and larg...

  5. A growing social network model in geographical space

    Science.gov (United States)

    Antonioni, Alberto; Tomassini, Marco

    2017-09-01

    In this work we propose a new model for the generation of social networks that includes their often ignored spatial aspects. The model is a growing one and links are created either taking space into account, or disregarding space and only considering the degree of target nodes. These two effects can be mixed linearly in arbitrary proportions through a parameter. We numerically show that for a given range of the combination parameter, and for given mean degree, the generated network class shares many important statistical features with those observed in actual social networks, including the spatial dependence of connections. Moreover, we show that the model provides a good qualitative fit to some measured social networks.

  6. Coupling entropy of co-processing model on social networks

    Science.gov (United States)

    Zhang, Zhanli

    2015-08-01

    Coupling entropy of co-processing model on social networks is investigated in this paper. As one crucial factor to determine the processing ability of nodes, the information flow with potential time lag is modeled by co-processing diffusion which couples the continuous time processing and the discrete diffusing dynamics. Exact results on master equation and stationary state are achieved to disclose the formation. In order to understand the evolution of the co-processing and design the optimal routing strategy according to the maximal entropic diffusion on networks, we propose the coupling entropy comprehending the structural characteristics and information propagation on social network. Based on the analysis of the co-processing model, we analyze the coupling impact of the structural factor and information propagating factor on the coupling entropy, where the analytical results fit well with the numerical ones on scale-free social networks.

  7. Analysis of organizational culture with social network models

    OpenAIRE

    Titov, S.

    2015-01-01

    Organizational culture is nowadays an object of numerous scientific papers. However, only marginal part of existing research attempts to use the formal models of organizational cultures. The lack of organizational culture models significantly limits the further research in this area and restricts the application of the theory to practice of organizational culture change projects. The article consists of general views on potential application of network models and social network analysis to th...

  8. Modelling animal group fission using social network dynamics.

    Science.gov (United States)

    Sueur, Cédric; Maire, Anaïs

    2014-01-01

    Group life involves both advantages and disadvantages, meaning that individuals have to compromise between their nutritional needs and their social links. When a compromise is impossible, the group splits in order to reduce conflict of interests and favour positive social interactions between its members. In this study we built a dynamic model of social networks to represent a succession of temporary fissions involving a change in social relations that could potentially lead to irreversible group fission (i.e. no more group fusion). This is the first study that assesses how a social network changes according to group fission-fusion dynamics. We built a model that was based on different parameters: the group size, the influence of nutritional needs compared to social needs, and the changes in the social network after a temporary fission. The results obtained from this theoretical data indicate how the percentage of social relation transfer, the number of individuals and the relative importance of nutritional requirements and social links influence the average number of days before irreversible fission occurs. The greater the nutritional needs and the higher the transfer of social relations during temporary fission, the fewer days will be observed before an irreversible fission. It is crucial to bridge the gap between the individual and the population level if we hope to understand how simple, local interactions may drive ecological systems.

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    J. A. Astaiza

    2015-12-01

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

  11. Models, Entropy and Information of Temporal Social Networks

    Science.gov (United States)

    Zhao, Kun; Karsai, Márton; Bianconi, Ginestra

    Temporal social networks are characterized by heterogeneous duration of contacts, which can either follow a power-law distribution, such as in face-to-face interactions, or a Weibull distribution, such as in mobile-phone communication. Here we model the dynamics of face-to-face interaction and mobile phone communication by a reinforcement dynamics, which explains the data observed in these different types of social interactions. We quantify the information encoded in the dynamics of these networks by the entropy of temporal networks. Finally, we show evidence that human dynamics is able to modulate the information present in social network dynamics when it follows circadian rhythms and when it is interfacing with a new technology such as the mobile-phone communication technology.

  12. Models, Entropy and Information of Temporal Social Networks

    CERN Document Server

    Zhao, Kun; Bianconi, Ginestra

    2013-01-01

    Temporal social networks are characterized by {heterogeneous} duration of contacts, which can either follow a power-law distribution, such as in face-to-face interactions, or a Weibull distribution, such as in mobile-phone communication. Here we model the dynamics of face-to-face interaction and mobile phone communication by a reinforcement dynamics, which explains the data observed in these different types of social interactions. We quantify the information encoded in the dynamics of these networks by the entropy of temporal networks. Finally, we show evidence that human dynamics is able to modulate the information present in social network dynamics when it follows circadian rhythms and when it is interfacing with a new technology such as the mobile-phone communication technology.

  13. A Stochastic Evolutionary Growth Model for Social Networks

    CERN Document Server

    Fenner, T; Loizou, G; Roussos, G; Fenner, Trevor; Levene, Mark; Loizou, George; Roussos, George

    2006-01-01

    We present a stochastic model for a social network, where new actors may join the network, existing actors may become inactive and, at a later stage, reactivate themselves. Our model captures the evolution of the network, assuming that actors attain new relations or become active according to the preferential attachment rule. We derive the mean-field equations for this stochastic model and show that, asymptotically, the distribution of actors obeys a power-law distribution. In particular, the model applies to social networks such as wireless local area networks, where users connect to access-points, and peer-to-peer networks where users connect to each other. As a proof of concept, we demonstrate the validity of our model empirically by analysing a public log containing traces from a wireless network at Dartmouth College over a period of three years. Analysing the data processed according to our model, we demonstrate that the distribution of user accesses is asymptotically a power-law distribution.

  14. A Social Network Model Exhibiting Tunable Overlapping Community Structure

    NARCIS (Netherlands)

    Liu, D.; Blenn, N.; Van Mieghem, P.F.A.

    2012-01-01

    Social networks, as well as many other real-world networks, exhibit overlapping community structure. In this paper, we present formulas which facilitate the computation for characterizing the overlapping community structure of networks. A hypergraph representation of networks with overlapping

  15. Rumor spreading model with noise interference in complex social networks

    Science.gov (United States)

    Zhu, Liang; Wang, Youguo

    2017-03-01

    In this paper, a modified susceptible-infected-removed (SIR) model has been proposed to explore rumor diffusion on complex social networks. We take variation of connectivity into consideration and assume the variation as noise. On the basis of related literature on virus networks, the noise is described as standard Brownian motion while stochastic differential equations (SDE) have been derived to characterize dynamics of rumor diffusion both on homogeneous networks and heterogeneous networks. Then, theoretical analysis on homogeneous networks has been demonstrated to investigate the solution of SDE model and the steady state of rumor diffusion. Simulations both on Barabási-Albert (BA) network and Watts-Strogatz (WS) network display that the addition of noise accelerates rumor diffusion and expands diffusion size, meanwhile, the spreading speed on BA network is much faster than on WS network under the same noise intensity. In addition, there exists a rumor diffusion threshold in statistical average meaning on homogeneous network which is absent on heterogeneous network. Finally, we find a positive correlation between peak value of infected individuals and noise intensity while a negative correlation between rumor lifecycle and noise intensity overall.

  16. Trust Model for Social Network using Singular Value Decomposition

    OpenAIRE

    Davis Bundi Ntwiga; Patrick Weke; Michael Kiura Kirumbu

    2016-01-01

    For effective interactions to take place in a social network, trust is important. We model trust of agents using the peer to peer reputation ratings in the network that forms a real valued matrix. Singular value decomposition discounts the reputation ratings to estimate the trust levels as trust is the subjective probability of future expectations based on current reputation ratings. Reputation and trust are closely related and singular value decomposition can estimate trust using the...

  17. Reconstruction of social group networks from friendship networks using a tag-based model

    Science.gov (United States)

    Guan, Yuan-Pan; You, Zhi-Qiang; Han, Xiao-Pu

    2016-12-01

    Social group is a type of mesoscopic structure that connects human individuals in microscopic level and the global structure of society. In this paper, we propose a tag-based model considering that social groups expand along the edge that connects two neighbors with a similar tag of interest. The model runs on a real-world friendship network, and its simulation results show that various properties of simulated group network can well fit the empirical analysis on real-world social groups, indicating that the model catches the major mechanism driving the evolution of social groups and successfully reconstructs the social group network from a friendship network and throws light on digging of relationships between social functional organizations.

  18. 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

  19. Evaluation Model for Experts Social Networks (Based on Case Study

    Directory of Open Access Journals (Sweden)

    Fatemeh Saghafi

    2012-05-01

    Full Text Available Every Social network is considered as a structured Society constitute of individual or organizational group which are associated together within different type of dependency. The most important elements influence the success of such social network is the level of interest for sharing the information. This article addresses the important factors on assessment of Intellectual National Internet Network(ININ. For assessment we propose Enhanced technology acceptance model which we deployed by extending Davis TAM(technology acceptance model.ININ is a web base sites for think thanking of researchers which is acting within a four month at RICT(Research institute of ICT and the number of 214 ICT researchers distribute and delivered their experience. The result shows that in intellectual society, Intelligence has higher values to be disseminated and higher inspiration is needed for its successful sharing in new generation of Information technology.

  20. Hypergraph model of social tagging networks

    CERN Document Server

    Zhang, Zi-Ke

    2010-01-01

    The past few years have witnessed the great success of a new family of paradigms, so-called folksonomy, which allows users to freely associate tags to resources and efficiently manage them. In order to uncover the underlying structures and user behaviors in folksonomy, in this paper, we propose an evolutionary hypergrah model to explain the emerging statistical properties. The present model introduces a novel mechanism that one can not only assign tags to resources, but also retrieve resources via collaborative tags. We then compare the model with a real-world dataset: \\emph{Del.icio.us}. Indeed, the present model shows considerable agreement with the empirical data in following aspects: power-law hyperdegree distributions, negtive correlation between clustering coefficients and hyperdegrees, and small average distances. Furthermore, the model indicates that most tagging behaviors are motivated by labeling tags to resources, and tags play a significant role in effectively retrieving interesting resources and ...

  1. A hypergraph model of social tagging networks

    Science.gov (United States)

    Zhang, Zi-Ke; Liu, Chuang

    2010-10-01

    The past few years have witnessed the great success of a new family of paradigms, so-called folksonomy, which allows users to freely associate tags with resources and efficiently manage them. In order to uncover the underlying structures and user behaviors in folksonomy, in this paper, we propose an evolutionary hypergraph model for explaining the emerging statistical properties. The present model introduces a novel mechanism that can not only assign tags to resources, but also retrieve resources via collaborative tags. We then compare the model with a real-world data set: Del.icio.us. Indeed, the present model shows considerable agreement with the empirical data in the following aspects: power-law hyperdegree distributions, negative correlation between clustering coefficients and hyperdegrees, and small average distances. Furthermore, the model indicates that most tagging behaviors are motivated by labeling tags on resources, and the tag plays a significant role in effectively retrieving interesting resources and making acquaintances with congenial friends. The proposed model may shed some light on the in-depth understanding of the structure and function of folksonomy.

  2. a Model for Brand Competition Within a Social Network

    Science.gov (United States)

    Huerta-Quintanilla, R.; Canto-Lugo, E.; Rodríguez-Achach, M.

    An agent-based model was built representing an economic environment in which m brands are competing for a product market. These agents represent companies that interact within a social network in which a certain agent persuades others to update or shift their brands; the brands of the products they are using. Decision rules were established that caused each agent to react according to the economic benefits it would receive; they updated/shifted only if it was beneficial. Each agent can have only one of the m possible brands, and she can interact with its two nearest neighbors and another set of agents which are chosen according to a particular set of rules in the network topology. An absorbing state was always reached in which a single brand monopolized the network (known as condensation). The condensation time varied as a function of model parameters is studied including an analysis of brand competition using different networks.

  3. Modeling the Relationship Between Social Network Activity, Inactivity, and Growth

    CERN Document Server

    Ribeiro, Bruno

    2013-01-01

    Online Social Networks (OSNs) are multi-billion dollar enterprises. Surprisingly, little is known about the mechanisms that drive them to growth, stability, or death. This study sheds light on these mechanisms. We are particularly interested in OSNs where current subscribers can invite new users to join the network (e.g., Facebook, LinkedIn). Measuring the relationship between subscriber activity and network growth of a large OSN over five years, we formulate three hypotheses that together describe the observed OSN subscriber behavior. We then provide a model (and extensions) that simultaneously satisfies all three hypotheses. Our model provides deep insights into the dynamics of subscriber activity, inactivity, and network growth rates, even predicting four types of OSNs with respect to subscriber activity evolution. Finally, we present activity data of nearly thirty OSN websites, measured over five years, and show that the observed activity is well described by one of the four activity time series predicted...

  4. Wayfinding in Social Networks

    Science.gov (United States)

    Liben-Nowell, David

    With the recent explosion of popularity of commercial social-networking sites like Facebook and MySpace, the size of social networks that can be studied scientifically has passed from the scale traditionally studied by sociologists and anthropologists to the scale of networks more typically studied by computer scientists. In this chapter, I will highlight a recent line of computational research into the modeling and analysis of the small-world phenomenon - the observation that typical pairs of people in a social network are connected by very short chains of intermediate friends - and the ability of members of a large social network to collectively find efficient routes to reach individuals in the network. I will survey several recent mathematical models of social networks that account for these phenomena, with an emphasis on both the provable properties of these social-network models and the empirical validation of the models against real large-scale social-network data.

  5. Multi-Topic Tracking Model for dynamic social network

    Science.gov (United States)

    Li, Yuhua; Liu, Changzheng; Zhao, Ming; Li, Ruixuan; Xiao, Hailing; Wang, Kai; Zhang, Jun

    2016-07-01

    The topic tracking problem has attracted much attention in the last decades. However, existing approaches rarely consider network structures and textual topics together. In this paper, we propose a novel statistical model based on dynamic bayesian network, namely Multi-Topic Tracking Model for Dynamic Social Network (MTTD). It takes influence phenomenon, selection phenomenon, document generative process and the evolution of textual topics into account. Specifically, in our MTTD model, Gibbs Random Field is defined to model the influence of historical status of users in the network and the interdependency between them in order to consider the influence phenomenon. To address the selection phenomenon, a stochastic block model is used to model the link generation process based on the users' interests to topics. Probabilistic Latent Semantic Analysis (PLSA) is used to describe the document generative process according to the users' interests. Finally, the dependence on the historical topic status is also considered to ensure the continuity of the topic itself in topic evolution model. Expectation Maximization (EM) algorithm is utilized to estimate parameters in the proposed MTTD model. Empirical experiments on real datasets show that the MTTD model performs better than Popular Event Tracking (PET) and Dynamic Topic Model (DTM) in generalization performance, topic interpretability performance, topic content evolution and topic popularity evolution performance.

  6. Modelling opinion formation driven communities in social networks

    CERN Document Server

    Iñiguez, Gerardo; Kertész, János; Kaski, Kimmo K

    2010-01-01

    In a previous paper we proposed a model to study the dynamics of opinion formation in human societies by a co-evolution process involving two distinct time scales of fast transaction and slower network evolution dynamics. In the transaction dynamics we take into account short range interactions as discussions between individuals and long range interactions to describe the attitude to the overall mood of society. The latter is handled by a uniformly distributed parameter $\\alpha$, assigned randomly to each individual, as quenched personal bias. The network evolution dynamics is realized by rewiring the societal network due to state variable changes as a result of transaction dynamics. The main consequence of this complex dynamics is that communities emerge in the social network for a range of values in the ratio between time scales. In this paper we focus our attention on the attitude parameter $\\alpha$ and its influence on the conformation of opinion and the size of the resulting communities. We present numer...

  7. Social Networks and Choice Set Formation in Discrete Choice Models

    Directory of Open Access Journals (Sweden)

    Bruno Wichmann

    2016-10-01

    Full Text Available The discrete choice literature has evolved from the analysis of a choice of a single item from a fixed choice set to the incorporation of a vast array of more complex representations of preferences and choice set formation processes into choice models. Modern discrete choice models include rich specifications of heterogeneity, multi-stage processing for choice set determination, dynamics, and other elements. However, discrete choice models still largely represent socially isolated choice processes —individuals are not affected by the preferences of choices of other individuals. There is a developing literature on the impact of social networks on preferences or the utility function in a random utility model but little examination of such processes for choice set formation. There is also emerging evidence in the marketplace of the influence of friends on choice sets and choices. In this paper we develop discrete choice models that incorporate formal social network structures into the choice set formation process in a two-stage random utility framework. We assess models where peers may affect not only the alternatives that individuals consider or include in their choice sets, but also consumption choices. We explore the properties of our models and evaluate the extent of “errors” in assessment of preferences, economic welfare measures and market shares if network effects are present, but are not accounted for in the econometric model. Our results shed light on the importance of the evaluation of peer or network effects on inclusion/exclusion of alternatives in a random utility choice framework.

  8. Multiple-membership multiple-classification models for social network and group dependences

    OpenAIRE

    Tranmer, Mark; Steel, David; Browne, William J

    2014-01-01

    The social network literature on network dependences has largely ignored other sources of dependence, such as the school that a student attends, or the area in which an individual lives. The multilevel modelling literature on school and area dependences has, in turn, largely ignored social networks. To bridge this divide, a multiple-membership multiple-classification modelling approach for jointly investigating social network and group dependences is presented. This allows social network and ...

  9. 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

  10. Modeling Evolutionary Dynamics of Lurking in Social Networks

    CERN Document Server

    Javarone, Marco Alberto; Tagarelli, Andrea

    2016-01-01

    Lurking is a complex user-behavioral phenomenon that occurs in all large-scale online communities and social networks. It generally refers to the behavior characterizing users that benefit from the information produced by others in the community without actively contributing back to the production of social content. The amount and evolution of lurkers may strongly affect an online social environment, therefore understanding the lurking dynamics and identifying strategies to curb this trend are relevant problems. In this regard, we introduce the Lurker Game, i.e., a model for analyzing the transitions from a lurking to a non-lurking (i.e., active) user role, and vice versa, in terms of evolutionary game theory. We evaluate the proposed Lurker Game by arranging agents on complex networks and analyzing the system evolution, seeking relations between the network topology and the final equilibrium of the game. Results suggest that the Lurker Game is suitable to model the lurking dynamics, showing how the adoption ...

  11. Modeling Verdict Outcomes Using Social Network Measures: The Watergate and Caviar Network Cases.

    Directory of Open Access Journals (Sweden)

    Víctor Hugo Masías

    Full Text Available Modelling criminal trial verdict outcomes using social network measures is an emerging research area in quantitative criminology. Few studies have yet analyzed which of these measures are the most important for verdict modelling or which data classification techniques perform best for this application. To compare the performance of different techniques in classifying members of a criminal network, this article applies three different machine learning classifiers-Logistic Regression, Naïve Bayes and Random Forest-with a range of social network measures and the necessary databases to model the verdicts in two real-world cases: the U.S. Watergate Conspiracy of the 1970's and the now-defunct Canada-based international drug trafficking ring known as the Caviar Network. In both cases it was found that the Random Forest classifier did better than either Logistic Regression or Naïve Bayes, and its superior performance was statistically significant. This being so, Random Forest was used not only for classification but also to assess the importance of the measures. For the Watergate case, the most important one proved to be betweenness centrality while for the Caviar Network, it was the effective size of the network. These results are significant because they show that an approach combining machine learning with social network analysis not only can generate accurate classification models but also helps quantify the importance social network variables in modelling verdict outcomes. We conclude our analysis with a discussion and some suggestions for future work in verdict modelling using social network measures.

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

    Science.gov (United States)

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

    2017-10-01

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

  13. Models of Charity Donations and Project Funding in Social Networks

    Science.gov (United States)

    Wojciechowski, Adam

    One of the key fundaments of building a society is common interest or shared aims of the group members. This research work is a try to analyze web-based services oriented towards money collection for various social and charity projects. The phenomenon of social founding is worth a closer look at because its success strongly depends on the ability to build an ad-hoc or persistent groups of people sharing their believes and willing to support external institutions or individuals. The paper presents a review of money collection sites, various models of donation and money collection process as well as ways how the projects' results are reported to their founders. There is also a proposal of money collection service, where donators are not charged until total declared help overheads required resources to complete the project. The risk of missing real donations for declared payments, after the collection is closed, can be assessed and minimized by building a social network.

  14. Modeling Access Control Policy of a Social Network

    Directory of Open Access Journals (Sweden)

    Chaimaa Belbergui

    2016-06-01

    Full Text Available Social networks bring together users in a virtual platform and offer them the ability to share -within the Community- personal and professional information’s, photos, etc. which are sometimes sensitive. Although, the majority of these networks provide access control mechanisms to their users (to manage who accesses to which information, privacy settings are limited and do not respond to all users' needs. Hence, the published information remain all vulnerable to illegal access. In this paper, the access control policy of the social network "Facebook" is analyzed in a profound way by starting with its modeling with "Organization Role Based Access Control" model, and moving to the simulation of the policy with an appropriate simulator to test the coherence aspect, and ending with a discussion of analysis results which shows the gap between access control management options offered by Facebook and the real requirements of users in the same context. Extracted conclusions prove the need of developing a new access control model that meets most of these requirements, which will be the subject of a forthcoming work.

  15. Evolution of Social networks

    OpenAIRE

    Hellmann, Tim; Staudigl, Mathias

    2012-01-01

    Modeling the evolution of networks is central to our understanding of modern large communication systems, such as theWorld-Wide-Web, as well as economic and social networks. The research on social and economic networks is truly interdisciplinary and the number of modeling strategies and concepts is enormous. In this survey we present some modeling approaches, covering classical random graph models and game-theoretic models, which may be used to provide a unified framework to model and analyze...

  16. Visualization Through Knowledge Representation Model for Social Networks

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar; Athar Javed, Muhammad; Ahmed, Zaki

    2011-01-01

    the process of knowing, learning and creating knowledge is the relevant aspect (Nonaka and Takeuchi 1995). In this paper knowledge representation is presented in 3D style for the understanding and visualization of dynamics of complex social networks by developing a TANetworkTool (Task Analysis Network Tool......). The standard or normal representation of a typical social network is through a graph data structure in 2D. The dynamics of larger social networks is so complex some time it becomes difficult to understand the various levels of interactions and dependencies just by mere representation through a tree or graph...... of complex social networks and complimenting the analytical results. This representation can also help authorities not necessarily having specific scientific background to understand and perhaps take preventive actions required in certain specific scenarios for example dealing with terrorist/covert networks....

  17. 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.

  18. Asymptotic analysis of threshold models for social networks

    CERN Document Server

    Garulli, Andrea

    2016-01-01

    A class of dynamic threshold models is proposed, for describing the upset of collective actions in social networks. The agents of the network have to decide whether to undertake a certain action or not. They make their decision by comparing the activity level of their neighbors with a time-varying threshold, evolving according to a time-invariant opinion dynamic model. Key features of the model are a parameter representing the degree of self-confidence of the agents, and the mechanism adopted by the agents to evaluate the activity level of their neighbors. The case in which a radical agent, initially eager to undertake the action, interacts with a group of ordinary agents, is considered. The main contribution of the paper is the complete analytic characterization of the asymptotic behaviors of the network, for three different graph topologies. The asymptotic activity patterns are determined as a function of the self-confidence parameter and of the initial threshold of the ordinary agents.

  19. A context-sensitive trust model for online social networking

    CSIR Research Space (South Africa)

    Danny, MN

    2016-11-01

    Full Text Available In Social Networking Sites (SNSs), users tend to accept friend requests and share their personal information based on intuitive trust levels. Mistakenly trusting and sharing private information with malicious users may lead to a wide variety...

  20. Social networks and trade of services: modelling interregional flows with spatial and network autocorrelation effects

    Science.gov (United States)

    de la Mata, Tamara; Llano, Carlos

    2013-07-01

    Recent literature on border effect has fostered research on informal barriers to trade and the role played by network dependencies. In relation to social networks, it has been shown that intensity of trade in goods is positively correlated with migration flows between pairs of countries/regions. In this article, we investigate whether such a relation also holds for interregional trade of services. We also consider whether interregional trade flows in services linked with tourism exhibit spatial and/or social network dependence. Conventional empirical gravity models assume the magnitude of bilateral flows between regions is independent of flows to/from regions located nearby in space, or flows to/from regions related through social/cultural/ethic network connections. With this aim, we provide estimates from a set of gravity models showing evidence of statistically significant spatial and network (demographic) dependence in the bilateral flows of the trade of services considered. The analysis has been applied to the Spanish intra- and interregional monetary flows of services from the accommodation, restaurants and travel agencies for the period 2000-2009, using alternative datasets for the migration stocks and definitions of network effects.

  1. Visualization Through Knowledge Representation Model for Social Networks

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar; Athar Javed, Muhammad; Ahmed, Zaki

    2011-01-01

    the process of knowing, learning and creating knowledge is the relevant aspect (Nonaka and Takeuchi 1995). In this paper knowledge representation is presented in 3D style for the understanding and visualization of dynamics of complex social networks by developing a TANetworkTool (Task Analysis Network Tool....... Although, many analytical methods provide relationship dependencies, role of different nodes and their importance in the network. In this paper we are presenting a visualization of networks by rotating the network through various dimensions to provide a more realistic view to understand the dynamics...

  2. Coevolving complex networks in the model of social interactions

    Science.gov (United States)

    Raducha, Tomasz; Gubiec, Tomasz

    2017-04-01

    We analyze Axelrod's model of social interactions on coevolving complex networks. We introduce four extensions with different mechanisms of edge rewiring. The models are intended to catch two kinds of interactions-preferential attachment, which can be observed in scientists or actors collaborations, and local rewiring, which can be observed in friendship formation in everyday relations. Numerical simulations show that proposed dynamics can lead to the power-law distribution of nodes' degree and high value of the clustering coefficient, while still retaining the small-world effect in three models. All models are characterized by two phase transitions of a different nature. In case of local rewiring we obtain order-disorder discontinuous phase transition even in the thermodynamic limit, while in case of long-distance switching discontinuity disappears in the thermodynamic limit, leaving one continuous phase transition. In addition, we discover a new and universal characteristic of the second transition point-an abrupt increase of the clustering coefficient, due to formation of many small complete subgraphs inside the network.

  3. From calls to communities: a model for time varying social networks

    CERN Document Server

    Laurent, Guillaume; Karsai, Márton

    2015-01-01

    Social interactions vary in time and appear to be driven by intrinsic mechanisms, which in turn shape the emerging structure of the social network. Large-scale empirical observations of social interaction structure have become possible only recently, and modelling their dynamics is an actual challenge. Here we propose a temporal network model which builds on the framework of activity-driven time-varying networks with memory. The model also integrates key mechanisms that drive the formation of social ties - social reinforcement, focal closure and cyclic closure, which have been shown to give rise to community structure and the global connectedness of the network. We compare the proposed model with a real-world time-varying network of mobile phone communication and show that they share several characteristics from heterogeneous degrees and weights to rich community structure. Further, the strong and weak ties that emerge from the model follow similar weight-topology correlations as real-world social networks, i...

  4. A Theoretical Model for Understanding the Dynamics of Online Social Networks Decay

    CERN Document Server

    Abufouda, Mohammed

    2016-01-01

    Online social networks represent a main source of communication and information exchange in today's life. They facilitate exquisitely news sharing, knowledge elicitation, and forming groups of same interests. Researchers in the last two decades studied the growth dynamics of the online social networks extensively questing a clear understanding of the behavior of humans in online social networks that helps in many directions, like engineering better recommendation systems and attracting new members. However, not all of social networks achieved the desired growth, for example, online social networks like MySpace, Orkut, and Friendster are out of service today. In this work, we present a probabilistic theoretical model that captures the dynamics of the social decay due to the inactivity of the members of a social network. The model is proved to have some interesting mathematical properties, namely \\textit{submodularity}, which imply achieving the model optimization in a reasonable performance. That means the max...

  5. Popularity Evaluation Model for Microbloggers Online Social Network

    Directory of Open Access Journals (Sweden)

    Xia Zhang

    2014-01-01

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

  6. The specification of weight structures in network autocorrelation models of social influence

    NARCIS (Netherlands)

    Leenders, Roger Th.A.J.

    2002-01-01

    Many physical and social phenomena are embedded within networks of interdependencies, the so-called 'context' of these phenomena. In network analysis, this type of process is typically modeled as a network autocorrelation model. Parameter estimates and inferences based on autocorrelation models, hin

  7. Beyond Dyadic Interdependence: Actor-Oriented Models for Co-Evolving Social Networks and Individual Behaviors

    Science.gov (United States)

    Burk, William J.; Steglich, Christian E. G.; Snijders, Tom A. B.

    2007-01-01

    Actor-oriented models are described as a longitudinal strategy for examining the co-evolution of social networks and individual behaviors. We argue that these models provide advantages over conventional approaches due to their ability to account for inherent dependencies between individuals embedded in a social network (i.e., reciprocity,…

  8. The Analysis of Social Networks.

    Science.gov (United States)

    O'Malley, A James; Marsden, Peter V

    2008-12-01

    Many questions about the social organization of medicine and health services involve interdependencies among social actors that may be depicted by networks of relationships. Social network studies have been pursued for some time in social science disciplines, where numerous descriptive methods for analyzing them have been proposed. More recently, interest in the analysis of social network data has grown among statisticians, who have developed more elaborate models and methods for fitting them to network data. This article reviews fundamentals of, and recent innovations in, social network analysis using a physician influence network as an example. After introducing forms of network data, basic network statistics, and common descriptive measures, it describes two distinct types of statistical models for network data: individual-outcome models in which networks enter the construction of explanatory variables, and relational models in which the network itself is a multivariate dependent variable. Complexities in estimating both types of models arise due to the complex correlation structures among outcome measures.

  9. Actor-network Procedures: Modeling Multi-factor Authentication, Device Pairing, Social Interactions

    Science.gov (United States)

    2011-08-29

    network model. The state of a configuration is thus the product of the states of its actors, where some of the actors only task is to store some values...Networks: How Social Production Transforms Markets and Freedom. Yale Univer- sity Press, 2006. [8] Bruno Blanchet. A computationally sound mechanized prover...and Caroline Haythornthwaite. Computer networks as social networks: Collaborative work, telework , and virtual community. Annual Review of Sociology, 22(1):213–238, 1996.

  10. Social Content Recommendation Based on Spatial-Temporal Aware Diffusion Modeling in Social Networks

    Directory of Open Access Journals (Sweden)

    Farman Ullah

    2016-09-01

    Full Text Available User interactions in online social networks (OSNs enable the spread of information and enhance the information dissemination process, but at the same time they exacerbate the information overload problem. In this paper, we propose a social content recommendation method based on spatial-temporal aware controlled information diffusion modeling in OSNs. Users interact more frequently when they are close to each other geographically, have similar behaviors, and fall into similar demographic categories. Considering these facts, we propose multicriteria-based social ties relationship and temporal-aware probabilistic information diffusion modeling for controlled information spread maximization in OSNs. The proposed social ties relationship modeling takes into account user spatial information, content trust, opinion similarity, and demographics. We suggest a ranking algorithm that considers the user ties strength with friends and friends-of-friends to rank users in OSNs and select highly influential injection nodes. These nodes are able to improve social content recommendations, minimize information diffusion time, and maximize information spread. Furthermore, the proposed temporal-aware probabilistic diffusion process categorizes the nodes and diffuses the recommended content to only those users who are highly influential and can enhance information dissemination. The experimental results show the effectiveness of the proposed scheme.

  11. Social network modeling: a powerful tool for the study of group scale phenomena in primates.

    Science.gov (United States)

    Jacobs, Armand; Petit, Odile

    2011-08-01

    Social Network Analysis is now a valuable tool to study social complexity in many animal species, including primates. However, this framework has rarely been used to implement quantitative data on the social structure of a group within computer models. Such approaches allow the investigation of how social organization constrains other traits and also how these traits can impact the social organization in return. In this commentary, we discuss the powerful potential of social network modeling as a way to study group scale phenomena in primates. We describe the advantages of using such a method and we focus on the specificity of this approach in primates, given the particularities of their social networks compared with those of other taxa. We also give practical considerations and a list of examples as for the choice of parameters that can be used to implement the social layer within the models.

  12. PageRank model of opinion formation on social networks

    Science.gov (United States)

    Kandiah, Vivek; Shepelyansky, Dima L.

    2012-11-01

    We propose the PageRank model of opinion formation and investigate its rich properties on real directed networks of the Universities of Cambridge and Oxford, LiveJournal, and Twitter. In this model, the opinion formation of linked electors is weighted with their PageRank probability. Such a probability is used by the Google search engine for ranking of web pages. We find that the society elite, corresponding to the top PageRank nodes, can impose its opinion on a significant fraction of the society. However, for a homogeneous distribution of two opinions, there exists a bistability range of opinions which depends on a conformist parameter characterizing the opinion formation. We find that the LiveJournal and Twitter networks have a stronger tendency to a totalitarian opinion formation than the university networks. We also analyze the Sznajd model generalized for scale-free networks with the weighted PageRank vote of electors.

  13. Self-Concealment, Social Network Sites Usage, Social Appearance Anxiety, Loneliness of High School Students: A Model Testing

    Science.gov (United States)

    Dogan, Ugur; Çolak, Tugba Seda

    2016-01-01

    This study was tested a model for explain to social networks sites (SNS) usage with structural equation modeling (SEM). Using SEM on a sample of 475 high school students (35% male, 65% female) students, model was investigated the relationship between self-concealment, social appearance anxiety, loneliness on SNS such as Twitter and Facebook usage.…

  14. Networking the seceder model: Group formation in social and economic systems

    Science.gov (United States)

    Grönlund, Andreas; Holme, Petter

    2004-09-01

    The seceder model illustrates how the desire to be different from the average can lead to formation of groups in a population. We turn the original, agent based, seceder model into a model of network evolution. We find that the structural characteristics of our model closely match empirical social networks. Statistics for the dynamics of group formation are also given. Extensions of the model to networks of companies are also discussed.

  15. Networking the seceder model: Group formation in social and economic systems

    CERN Document Server

    Grönlund, A

    2004-01-01

    The seceder model illustrates how the desire to be different than the average can lead to formation of groups in a population. We turn the original, agent based, seceder model into a model of network evolution. We find that the structural characteristics our model closely matches empirical social networks. Statistics for the dynamics of group formation are also given. Extensions of the model to networks of companies are also discussed.

  16. Affinity driven social networks

    Science.gov (United States)

    Ruyú, B.; Kuperman, M. N.

    2007-04-01

    In this work we present a model for evolving networks, where the driven force is related to the social affinity between individuals of a population. In the model, a set of individuals initially arranged on a regular ordered network and thus linked with their closest neighbors are allowed to rearrange their connections according to a dynamics closely related to that of the stable marriage problem. We show that the behavior of some topological properties of the resulting networks follows a non trivial pattern.

  17. PageRank model of opinion formation on social networks

    CERN Document Server

    Kandiah, Vivek

    2012-01-01

    We propose the PageRank model of opinion formation and investigate its rich properties on real directed networks of Universities of Cambridge and Oxford, LiveJournal and Twitter. In this model the opinion formation of linked electors is weighted with their PageRank probability. We find that the society elite, corresponding to the top PageRank nodes, can impose its opinion to a significant fraction of the society. However, for a homogeneous distribution of two opinions there exists a bistability range of opinions which depends on a conformist parameter characterizing the opinion formation. We find that LiveJournal and Twitter networks have a stronger tendency to a totalitar opinion formation. We also analyze the Sznajd model generalized for scale-free networks with the weighted PageRank vote of electors.

  18. 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

  19. 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...

  20. Rumor Spreading Model with Trust Mechanism in Complex Social Networks

    Institute of Scientific and Technical Information of China (English)

    WANG Ya-Qi; YANG Xiao-Yuan; HAN Yi-Liang; WANG Xu-An

    2013-01-01

    In this paper,to study rumor spreading,we propose a novel susceptible-infected-removed (SIR) model by introducing the trust mechanism.We derive mean-field equations that describe the dynamics of the SIR model on homogeneous networks and inhomogeneous networks.Then a steady-state analysis is conducted to investigate the critical threshold and the final size of the rumor spreading.We show that the introduction of trust mechanism reduces the final rumor size and the velocity of rumor spreading,but increases the critical thresholds on both networks.Moreover,the trust mechanism not only greatly reduces the maximum rumor influence,but also postpones the rumor terminal time,which provides us with more time to take measures to control the rumor spreading.The theoretical results are confirmed by sufficient numerical simulations.

  1. 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

  2. The Analysis of Social Networks

    OpenAIRE

    O’Malley, A James; Marsden, Peter V.

    2008-01-01

    Many questions about the social organization of medicine and health services involve interdependencies among social actors that may be depicted by networks of relationships. Social network studies have been pursued for some time in social science disciplines, where numerous descriptive methods for analyzing them have been proposed. More recently, interest in the analysis of social network data has grown among statisticians, who have developed more elaborate models and methods for fitting them...

  3. Systems approach to studying animal sociality: individual position versus group organization in dynamic social network models.

    Directory of Open Access Journals (Sweden)

    Karlo Hock

    Full Text Available Social networks can be used to represent group structure as a network of interacting components, and also to quantify both the position of each individual and the global properties of a group. In a series of simulation experiments based on dynamic social networks, we test the prediction that social behaviors that help individuals reach prominence within their social group may conflict with their potential to benefit from their social environment. In addition to cases where individuals were able to benefit from improving both their personal relative importance and group organization, using only simple rules of social affiliation we were able to obtain results in which individuals would face a trade-off between these factors. While selection would favor (or work against social behaviors that concordantly increase (or decrease, respectively fitness at both individual and group level, when these factors conflict with each other the eventual selective pressure would depend on the relative returns individuals get from their social environment and their position within it. The presented results highlight the importance of a systems approach to studying animal sociality, in which the effects of social behaviors should be viewed not only through the benefits that those provide to individuals, but also in terms of how they affect broader social environment and how in turn this is reflected back on an individual's fitness.

  4. Systems approach to studying animal sociality: individual position versus group organization in dynamic social network models.

    Science.gov (United States)

    Hock, Karlo; Ng, Kah Loon; Fefferman, Nina H

    2010-12-23

    Social networks can be used to represent group structure as a network of interacting components, and also to quantify both the position of each individual and the global properties of a group. In a series of simulation experiments based on dynamic social networks, we test the prediction that social behaviors that help individuals reach prominence within their social group may conflict with their potential to benefit from their social environment. In addition to cases where individuals were able to benefit from improving both their personal relative importance and group organization, using only simple rules of social affiliation we were able to obtain results in which individuals would face a trade-off between these factors. While selection would favor (or work against) social behaviors that concordantly increase (or decrease, respectively) fitness at both individual and group level, when these factors conflict with each other the eventual selective pressure would depend on the relative returns individuals get from their social environment and their position within it. The presented results highlight the importance of a systems approach to studying animal sociality, in which the effects of social behaviors should be viewed not only through the benefits that those provide to individuals, but also in terms of how they affect broader social environment and how in turn this is reflected back on an individual's fitness.

  5. Systems Approach to Studying Animal Sociality: Individual Position versus Group Organization in Dynamic Social Network Models

    Science.gov (United States)

    Hock, Karlo; Ng, Kah Loon; Fefferman, Nina H.

    2010-01-01

    Social networks can be used to represent group structure as a network of interacting components, and also to quantify both the position of each individual and the global properties of a group. In a series of simulation experiments based on dynamic social networks, we test the prediction that social behaviors that help individuals reach prominence within their social group may conflict with their potential to benefit from their social environment. In addition to cases where individuals were able to benefit from improving both their personal relative importance and group organization, using only simple rules of social affiliation we were able to obtain results in which individuals would face a trade-off between these factors. While selection would favor (or work against) social behaviors that concordantly increase (or decrease, respectively) fitness at both individual and group level, when these factors conflict with each other the eventual selective pressure would depend on the relative returns individuals get from their social environment and their position within it. The presented results highlight the importance of a systems approach to studying animal sociality, in which the effects of social behaviors should be viewed not only through the benefits that those provide to individuals, but also in terms of how they affect broader social environment and how in turn this is reflected back on an individual's fitness. PMID:21203425

  6. Online social support networks.

    Science.gov (United States)

    Mehta, Neil; Atreja, Ashish

    2015-04-01

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

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

    NARCIS (Netherlands)

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

    2010-01-01

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

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

    NARCIS (Netherlands)

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

    2008-01-01

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

  9. COSMODEL: AN INTERACTION MODEL FOR SOCIAL NETWORK GAMES

    Directory of Open Access Journals (Sweden)

    MIGUEL NIÑO

    2011-01-01

    Full Text Available Los juegos para redes sociales (videojuegos para redes sociales en línea, se han vuelto muy populares entre los desarrolladores de videojuegos. Sin embargo, los soportes conceptuales para los diseñadores de este tipo de juegos son escasos, en particular aquellos que se enfocan en la interacción entre jugadores. Debido a lo anterior, se propone CosModel como un modelo para el diseño de juegos para redes sociales. CosModel se compone de tres vistas de diseño de interacción que respaldan la construcción de estos juegos y se enfocan en potenciar las interacciones entre los jugadores. Una de estas vistas presenta el uso de una metáfora como ayuda conceptual para el diseño de juegos para redes sociales. Este artículo presenta el contexto teórico que apoya al modelo, el proceso de desarrollo del modelo y su estructura, y un proceso propuesto para su implementación.

  10. Modeling peer and external influence in online social networks

    CERN Document Server

    Piškorec, Matija; Miholić, Iva; Šmuc, Tomislav; Šikić, Mile

    2016-01-01

    Opinion polls mediated through a social network can give us, in addition to usual demographics data like age, gender and geographic location, a friendship structure between voters and the temporal dynamics of their activity during the voting process. Using a Facebook application we collected friendship relationships, demographics and votes of over ten thousand users on the referendum on the definition of marriage in Croatia held on 1st of December 2013. We also collected data on online news articles mentioning our application. Publication of these articles align closely with large peaks of voting activity, indicating that these external events have a crucial influence in engaging the voters. Also, existence of strongly connected friendship communities where majority of users vote during short time period, and the fact that majority of users in general tend to friend users that voted the same suggest that peer influence also has its role in engaging the voters. As we are not able to track activity of our users...

  11. 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.

  12. Probing models of information spreading in social networks

    CERN Document Server

    Zoller, J

    2014-01-01

    We apply signal processing analysis to the information spreading in scale-free network. To reproduce typical behaviors obtained from the analysis of information spreading in the world wide web we use a modified SIS model where synergy effects and influential nodes are taken into account. This model depends on a single free parameter that characterize the memory-time of the spreading process. We show that by means of fractal analysis it is possible -from aggregated easily accessible data- to gain information on the memory time of the underlying mechanism driving the information spreading process.

  13. Modeling the role of relationship fading and breakup in social network formation

    CERN Document Server

    Murase, Yohsuke; Török, János; Kertész, János; Kaski, Kimmo

    2015-01-01

    In social networks of human individuals, social relationships do not necessarily last forever as they can either fade gradually with time, resulting in link aging, or terminate abruptly, causing link deletion, as even old friendships may cease. In this paper, we study a social network formation model where we introduce several ways by which a link termination takes place. If we adopt the link aging, we get a more modular structure with more homogeneously distributed link weights within communities than when link deletion is used. By investigating distributions and relations of various network characteristics, we find that the empirical findings are better reproduced with the link deletion model. This indicates that link deletion plays a more prominent role in organizing social networks than link aging.

  14. Modelling the public opinion transmission on social networks under opinion leaders

    Science.gov (United States)

    Li, Zuozhi; Li, Meng; Ji, Wanwan

    2017-06-01

    In this paper, based on Social Network Analysis (SNA), the social network model of opinion leaders influencing the public opinion transmission is explored. The hot event, A Female Driver Was Beaten Due To Lane Change, has characteristics of individual short-term and non-government intervention, which is used to data extraction, and formed of the network structure on opinion leaders influencing the public opinion transmission. And the evolution mechanism are analyzed in the three evolutionary situations. Opinion leaders influence micro-blogging public opinion on social network evolution model shows that this type of network public opinion transmission is largely constrained by opinion leaders, so the opinion leaders behavior supervising on the spread of this public opinion is pivotal, and which has a guiding significance.

  15. USER-CENTRIC PERSONALIZED MULTIFACET MODEL TRUST IN ONLINE SOCIAL NETWORK

    Directory of Open Access Journals (Sweden)

    Liu Ban Chieng

    2014-12-01

    Full Text Available Online Social Network (OSN has become the most popular platform on the Internet that can provide an interesting and creative ways to communicate, sharing and meets with peoples. As OSNs mature, issues regarding proper use of OSNs are also growing. In this research, the challenges of online social networks have been investigated. The current issues in some of the Social Network Sites are being studied and compared. Cyber criminals, malware attacks, physical threat, security and usability and some privacy issues have been recognized as the challenges of the current social networking sites. Trust concerns have been raised and the trustworthiness of social networking sites has been questioned. Currently, the trust in social networks is using the single- faceted approach, which is not well personalized, and doesn’t account for the subjective views of trust, according to each user, but only the general trust believes of a group of population. The trust level towards a person cannot be calculated and trust is lack of personalization. From our initial survey, we had found that most people can share their information without any doubts on OSN but they normally do not trust all their friends equally and think there is a need of trust management. We had found mixed opinions in relation to the proposed rating feature in OSNs too. By adopting the idea of multi-faceted trust model, a user-centric model that can personalize the comments/photos in social network with user’s customized traits of trust is proposed. This model can probably solve many of the trust issues towards the social networking sites with personalized trust features, in order to keep the postings on social sites confidential and integrity.

  16. Dynamic vs. static social networks in models of parasite transmission: predicting Cryptosporidium spread in wild lemurs.

    Science.gov (United States)

    Springer, Andrea; Kappeler, Peter M; Nunn, Charles L

    2016-12-14

    Social networks provide an established tool to implement heterogeneous contact structures in epidemiological models. Dynamic temporal changes in contact structure and ranging behaviour of wildlife may impact disease dynamics. A consensus has yet to emerge, however, concerning the conditions in which network dynamics impact model outcomes, as compared to static approximations that average contact rates over longer time periods. Furthermore, as many pathogens can be transmitted both environmentally and via close contact, it is important to investigate the relative influence of both transmission routes in real-world populations. Here, we use empirically derived networks from a population of wild primates, Verreaux's sifakas (Propithecus verreauxi), and simulated networks to investigate pathogen spread in dynamic vs. static social networks. First, we constructed a susceptible-exposed-infected-recovered model of Cryptosporidium spread in wild Verreaux's sifakas. We incorporated social and environmental transmission routes and parameterized the model for two different climatic seasons. Second, we used simulated networks and greater variation in epidemiological parameters to investigate the conditions in which dynamic networks produce larger outbreak sizes than static networks. We found that average outbreak size of Cryptosporidium infections in sifakas was larger when the disease was introduced in the dry season than in the wet season, driven by an increase in home range overlap towards the end of the dry season. Regardless of season, dynamic networks always produced larger average outbreak sizes than static networks. Larger outbreaks in dynamic models based on simulated networks occurred especially when the probability of transmission and recovery were low. Variation in tie strength in the dynamic networks also had a major impact on outbreak size, while network modularity had a weaker influence than epidemiological parameters that determine transmission and recovery

  17. How Crime Spreads Through Imitation in Social Networks: A Simulation Model

    Science.gov (United States)

    Punzo, Valentina

    In this chapter an agent-based model for investigating how crime spreads through social networks is presented. Some theoretical issues related to the sociological explanation of crime are tested through simulation. The agent-based simulation allows us to investigate the relative impact of some mechanisms of social influence on crime, within a set of controlled simulated experiments.

  18. Friendship Dissolution Within Social Networks Modeled Through Multilevel Event History Analysis.

    Science.gov (United States)

    Dean, Danielle O; Bauer, Daniel J; Prinstein, Mitchell J

    2017-01-01

    A social network perspective can bring important insight into the processes that shape human behavior. Longitudinal social network data, measuring relations between individuals over time, has become increasingly common-as have the methods available to analyze such data. A friendship duration model utilizing discrete-time multilevel survival analysis with a multiple membership random effect structure is developed and applied here to study the processes leading to undirected friendship dissolution within a larger social network. While the modeling framework is introduced in terms of understanding friendship dissolution, it can be used to understand microlevel dynamics of a social network more generally. These models can be fit with standard generalized linear mixed-model software, after transforming the data to a pair-period data set. An empirical example highlights how the model can be applied to understand the processes leading to friendship dissolution between high school students, and a simulation study is used to test the use of the modeling framework under representative conditions that would be found in social network data. Advantages of the modeling framework are highlighted, and potential limitations and future directions are discussed.

  19. Social dynamics with peer support on heterogeneous networks: The "mafia model"

    CERN Document Server

    Gambra, Marta Balbás

    2011-01-01

    Human behavior often exhibit a scheme in which individuals adopt indifferent, neutral, or radical positions on a given topic. The mechanisms leading to community formation are strongly related with social pressure and the topology of the contact network. Here, we discuss an approach to model social behavior which accounts for the protection by alike peers proportional to their relative abundance in the closest neighborhood. We explore the ensuing non-linear dynamics emphasizing the role of the specific structure of the social network, modeled by scale-free graphs. We find that both coexistence of opinions and consensus on the default position are possible stationary states of the model. In particular, we show how these states critically depend on the heterogeneity of the social network and the specific distribution of external control elements.

  20. 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

  1. 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

  2. Tolerance-based interaction: a new model targeting opinion formation and diffusion in social networks

    Directory of Open Access Journals (Sweden)

    Alexandru Topirceanu

    2016-01-01

    Full Text Available One of the main motivations behind social network analysis is the quest for understanding opinion formation and diffusion. Previous models have limitations, as they typically assume opinion interaction mechanisms based on thresholds which are either fixed or evolve according to a random process that is external to the social agent. Indeed, our empirical analysis on large real-world datasets such as Twitter, Meme Tracker, and Yelp, uncovers previously unaccounted for dynamic phenomena at population-level, namely the existence of distinct opinion formation phases and social balancing. We also reveal that a phase transition from an erratic behavior to social balancing can be triggered by network topology and by the ratio of opinion sources. Consequently, in order to build a model that properly accounts for these phenomena, we propose a new (individual-level opinion interaction model based on tolerance. As opposed to the existing opinion interaction models, the new tolerance model assumes that individual’s inner willingness to accept new opinions evolves over time according to basic human traits. Finally, by employing discrete event simulation on diverse social network topologies, we validate our opinion interaction model and show that, although the network size and opinion source ratio are important, the phase transition to social balancing is mainly fostered by the democratic structure of the small-world topology.

  3. Social network analysis and network connectedness analysis for industrial symbiotic systems: model development and case study

    Institute of Scientific and Technical Information of China (English)

    Yan ZHANG; Hongmei ZHENG; Bin CHEN; Naijin YANG

    2013-01-01

    An important and practical pattern of industrial symbiosis is rapidly developing:eco-industrial parks.In this study,we used social network analysis to study the network connectedness (i.e.,the proportion of the theoretical number of connections that had been achieved) and related attributes of these hybrid ecological and industrial symbiotic systems.This approach provided insights into details of the network's interior and analyzed the overall degree of connectedness and the relationships among the nodes within the network.We then characterized the structural attributes of the network and subnetwork nodes at two levels (core and periphery),thereby providing insights into the operational problems within each eco-industrial park.We chose ten typical ecoindustrial parks in China and around the world and compared the degree of network connectedness of these systems that resulted from exchanges of products,byproducts,and wastes.By analyzing the density and nodal degree,we determined the relative power and status of the nodes in these networks,as well as other structural attributes such as the core-periphery structure and the degree of sub-network connectedness.The results reveal the operational problems created by the structure of the industrial networks and provide a basis for improving the degree of completeness,thereby increasing their potential for sustainable development and enriching the methods available for the study of industrial symbiosis.

  4. A model of social network formation under the impact of structural balance

    Science.gov (United States)

    Li, Pei; Cheng, Jiajun; Chen, Yingwen; Wang, Hui

    2016-03-01

    Social networks have attracted remarkable attention from both academic and industrial societies and it is of great importance to understand the formation of social networks. However, most existing research cannot be applied directly to investigate social networks, where relationships are heterogeneous and structural balance is a common phenomenon. In this paper, we take both positive and negative relationships into consideration and propose a model to characterize the process of social network formation under the impact of structural balance. In this model, a new node first establishes a link with an existing node and then tries to connect to each of the newly connected node’s neighbors. If a new link is established, the type of this link is determined by structural balance. Then we analyze the degree distribution of the generated network theoretically, and estimate the fractions of positive and negative links. All analysis results are verified by simulations. These results are of importance to understand the formation of social networks, and the model can be easily extended to consider more realistic situations.

  5. Identifying influential nodes in dynamic social networks based on degree-corrected stochastic block model

    Science.gov (United States)

    Wang, Tingting; Dai, Weidi; Jiao, Pengfei; Wang, Wenjun

    2016-05-01

    Many real-world data can be represented as dynamic networks which are the evolutionary networks with timestamps. Analyzing dynamic attributes is important to understanding the structures and functions of these complex networks. Especially, studying the influential nodes is significant to exploring and analyzing networks. In this paper, we propose a method to identify influential nodes in dynamic social networks based on identifying such nodes in the temporal communities which make up the dynamic networks. Firstly, we detect the community structures of all the snapshot networks based on the degree-corrected stochastic block model (DCBM). After getting the community structures, we capture the evolution of every community in the dynamic network by the extended Jaccard’s coefficient which is defined to map communities among all the snapshot networks. Then we obtain the initial influential nodes of the dynamic network and aggregate them based on three widely used centrality metrics. Experiments on real-world and synthetic datasets demonstrate that our method can identify influential nodes in dynamic networks accurately, at the same time, we also find some interesting phenomena and conclusions for those that have been validated in complex network or social science.

  6. Customer social network affects marketing strategy: A simulation analysis based on competitive diffusion model

    Science.gov (United States)

    Hou, Rui; Wu, Jiawen; Du, Helen S.

    2017-03-01

    To explain the competition phenomenon and results between QQ and MSN (China) in the Chinese instant messaging software market, this paper developed a new population competition model based on customer social network. The simulation results show that the firm whose product with greater network externality effect will gain more market share than its rival when the same marketing strategy is used. The firm with the advantage of time, derived from the initial scale effect will become more competitive than its rival when facing a group of common penguin customers within a social network, verifying the winner-take-all phenomenon in this case.

  7. Analysing animal social network dynamics: the potential of stochastic actor-oriented models.

    Science.gov (United States)

    Fisher, David N; Ilany, Amiyaal; Silk, Matthew J; Tregenza, Tom

    2017-03-01

    Animals are embedded in dynamically changing networks of relationships with conspecifics. These dynamic networks are fundamental aspects of their environment, creating selection on behaviours and other traits. However, most social network-based approaches in ecology are constrained to considering networks as static, despite several calls for such analyses to become more dynamic. There are a number of statistical analyses developed in the social sciences that are increasingly being applied to animal networks, of which stochastic actor-oriented models (SAOMs) are a principal example. SAOMs are a class of individual-based models designed to model transitions in networks between discrete time points, as influenced by network structure and covariates. It is not clear, however, how useful such techniques are to ecologists, and whether they are suited to animal social networks. We review the recent applications of SAOMs to animal networks, outlining findings and assessing the strengths and weaknesses of SAOMs when applied to animal rather than human networks. We go on to highlight the types of ecological and evolutionary processes that SAOMs can be used to study. SAOMs can include effects and covariates for individuals, dyads and populations, which can be constant or variable. This allows for the examination of a wide range of questions of interest to ecologists. However, high-resolution data are required, meaning SAOMs will not be useable in all study systems. It remains unclear how robust SAOMs are to missing data and uncertainty around social relationships. Ultimately, we encourage the careful application of SAOMs in appropriate systems, with dynamic network analyses likely to prove highly informative. Researchers can then extend the basic method to tackle a range of existing questions in ecology and explore novel lines of questioning. © 2016 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

  8. 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......Multilayer networks, in particular multilayer social networks, where users belong to and interact on different networks at the same time, are an active research area in social network analysis, computer science, and physics. These networks have traditionally been studied within these separate...

  9. Social networks enabled coordination model for cost management of patient hospital admissions.

    Science.gov (United States)

    Uddin, Mohammed Shahadat; Hossain, Liaquat

    2011-09-01

    In this study, we introduce a social networks enabled coordination model for exploring the effect of network position of "patient," "physician," and "hospital" actors in a patient-centered care network that evolves during patient hospitalization period on the total cost of coordination. An actor is a node, which represents an entity such as individual and organization in a social network. In our analysis of actor networks and coordination in the healthcare literature, we identified that there is significant gap where a number of promising hospital coordination model have been developed (e.g., Guided Care Model, Chronic Care Model) for the current healthcare system focusing on quality of service and patient satisfaction. The health insurance dataset for total hip replacement (THR) from hospital contribution fund, a prominent Australian Health Insurance Company, are analyzed to examine our proposed coordination model. We consider network attributes of degree, connectedness, in-degree, out-degree, and tie strength to measure network position of actors. To measure the cost of coordination for a particular hospital, average of total hospitalization expenses for all THR hospital admissions is used. Results show that network positions of "patient," "physician," and "hospital" actors considering all hospital admissions that a particular hospital has have effect on the average of total hospitalization expenses of that hospital. These results can be used as guidelines to set up a cost-effective healthcare practice structure for patient hospitalization expenses.

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

    OpenAIRE

    Chun Meng Tang; Miang Hong Ngerng

    2015-01-01

    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 co...

  11. Hierarchical winner-take-all particle swarm optimization social network for neural model fitting.

    Science.gov (United States)

    Coventry, Brandon S; Parthasarathy, Aravindakshan; Sommer, Alexandra L; Bartlett, Edward L

    2017-02-01

    Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models.

  12. The social networking application success model : An Empirical Study of Facebook and Twitter

    NARCIS (Netherlands)

    Ou, Carol; Davison, R.M.; Huang, Q.

    2016-01-01

    Social networking applications (SNAs) are among the fastest growing web applications of recent years. In this paper, we propose a causal model to assess the success of SNAs, grounded on DeLone and McLean’s updated information systems (IS) success model. In addition to their original three dimensions

  13. The social networking application success model : An empirical study of Facebook and Twitter

    NARCIS (Netherlands)

    Ou, Carol; Davison, R.M.; Huang, Q.

    2016-01-01

    Social networking applications (SNAs) are among the fastest growing web applications of recent years. In this paper, we propose a causal model to assess the success of SNAs, grounded on DeLone and McLean’s updated information systems (IS) success model. In addition to their original three dimensions

  14. Accelerating a Network Model of Care: Taking a Social Innovation to Scale

    Directory of Open Access Journals (Sweden)

    Kerry Byrne

    2012-07-01

    Full Text Available Government-funded systems of health and social care are facing enormous fiscal and human-resource challenges. The space for innovation in care is wide open and new disruptive patterns are emerging. These include self-management and personal budgets, participatory and integrated care, supported decision making and a renewed focus on prevention. Taking these disruptive patterns to scale can be accelerated by a technologically enabled shift to a network model of care to co-create the best outcomes for individuals, family caregivers, and health and social care organizations. The connections, relationships, and activities within an individual’s personal network lay the foundation for care that health and social care systems/policy must simultaneously support and draw on for positive outcomes. Practical tools, adequate information, and tangible resources are required to coordinate and sustain care. Tyze Personal Networks is a social venture that uses technology to engage and inform the individual, their personal networks, and their care providers to co-create the best outcomes. In this article, we demonstrate how Tyze contributes to a shift to a network model of care by strengthening our networks and enhancing partnerships between care providers, individuals, and family and friends.

  15. Integrating Entropy and Closed Frequent Pattern Mining for Social Network Modelling and Analysis

    Science.gov (United States)

    Adnan, Muhaimenul; Alhajj, Reda; Rokne, Jon

    The recent increase in the explicitly available social networks has attracted the attention of the research community to investigate how it would be possible to benefit from such a powerful model in producing effective solutions for problems in other domains where the social network is implicit; we argue that social networks do exist around us but the key issue is how to realize and analyze them. This chapter presents a novel approach for constructing a social network model by an integrated framework that first preparing the data to be analyzed and then applies entropy and frequent closed patterns mining for network construction. For a given problem, we first prepare the data by identifying items and transactions, which arc the basic ingredients for frequent closed patterns mining. Items arc main objects in the problem and a transaction is a set of items that could exist together at one time (e.g., items purchased in one visit to the supermarket). Transactions could be analyzed to discover frequent closed patterns using any of the well-known techniques. Frequent closed patterns have the advantage that they successfully grab the inherent information content of the dataset and is applicable to a broader set of domains. Entropies of the frequent closed patterns arc used to keep the dimensionality of the feature vectors to a reasonable size; it is a kind of feature reduction process. Finally, we analyze the dynamic behavior of the constructed social network. Experiments were conducted on a synthetic dataset and on the Enron corpus email dataset. The results presented in the chapter show that social networks extracted from a feature set as frequent closed patterns successfully carry the community structure information. Moreover, for the Enron email dataset, we present an analysis to dynamically indicate the deviations from each user's individual and community profile. These indications of deviations can be very useful to identify unusual events.

  16. 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.

  17. Time is of the essence: an application of a relational event model for animal social networks.

    Science.gov (United States)

    Patison, K P; Quintane, E; Swain, D L; Robins, G; Pattison, P

    Understanding how animal social relationships are created, maintained and severed has ecological and evolutionary significance. Animal social relationships are inferred from observations of interactions between animals; the pattern of interaction over time indicates the existence (or absence) of a social relationship. Autonomous behavioural recording technologies are increasingly being used to collect continuous interaction data on animal associations. However, continuous data sequences are typically aggregated to represent a relationship as part of one (or several) pictures of the network of relations among animals, in a way that parallels human social networks. This transformation entails loss of information about interaction timing and sequence, which are particularly important to understand the formation of relationships or their disruption. Here, we describe a new statistical model, termed the relational event model, that enables the analysis of fine-grained animal association data as a continuous time sequence without requiring aggregation of the data. We apply the model to a unique data set of interaction between familiar and unfamiliar steers during a series of 36 experiments to investigate the process of social disruption and relationship formation. We show how the model provides key insights into animal behaviour in terms of relationship building, the integration process of unfamiliar animals and group building dynamics. The relational event model is well suited to data structures that are common to animal behavioural studies and can therefore be applied to a range of social interaction data to understand animal social dynamics.

  18. Coupling ecological and social network models to assess "transmission" and "contagion" of an aquatic invasive species.

    Science.gov (United States)

    Haak, Danielle M; Fath, Brian D; Forbes, Valery E; Martin, Dustin R; Pope, Kevin L

    2017-04-01

    Network analysis is used to address diverse ecological, social, economic, and epidemiological questions, but few efforts have been made to combine these field-specific analyses into interdisciplinary approaches that effectively address how complex systems are interdependent and connected to one another. Identifying and understanding these cross-boundary connections improves natural resource management and promotes proactive, rather than reactive, decisions. This research had two main objectives; first, adapt the framework and approach of infectious disease network modeling so that it may be applied to the socio-ecological problem of spreading aquatic invasive species, and second, use this new coupled model to simulate the spread of the invasive Chinese mystery snail (Bellamya chinensis) in a reservoir network in Southeastern Nebraska, USA. The coupled model integrates an existing social network model of how anglers move on the landscape with new reservoir-specific ecological network models. This approach allowed us to identify 1) how angler movement among reservoirs aids in the spread of B. chinensis, 2) how B. chinensis alters energy flows within individual-reservoir food webs, and 3) a new method for assessing the spread of any number of non-native or invasive species within complex, social-ecological systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

  19. Modeling Social Influences in a Knowledge Management Network

    Science.gov (United States)

    Franco, Giacomo; Maresca, Paolo; Nota, Giancarlo

    2010-01-01

    The issue of knowledge management in a distributed network is receiving increasing attention from both scientific and industrial organizations. Research efforts in this field are motivated by the awareness that knowledge is more and more perceived as a primary economic resource and that, in the context of organization of organizations, the…

  20. Modeling Social Influences in a Knowledge Management Network

    Science.gov (United States)

    Franco, Giacomo; Maresca, Paolo; Nota, Giancarlo

    2010-01-01

    The issue of knowledge management in a distributed network is receiving increasing attention from both scientific and industrial organizations. Research efforts in this field are motivated by the awareness that knowledge is more and more perceived as a primary economic resource and that, in the context of organization of organizations, the…

  1. Network-oriented modeling addressing complexity of cognitive, affective and social interactions

    CERN Document Server

    Treur, Jan

    2016-01-01

    This book presents a new approach that can be applied to complex, integrated individual and social human processes. It provides an alternative means of addressing complexity, better suited for its purpose than and effectively complementing traditional strategies involving isolation and separation assumptions. Network-oriented modeling allows high-level cognitive, affective and social models in the form of (cyclic) graphs to be constructed, which can be automatically transformed into executable simulation models. The modeling format used makes it easy to take into account theories and findings about complex cognitive and social processes, which often involve dynamics based on interrelating cycles. Accordingly, it makes it possible to address complex phenomena such as the integration of emotions within cognitive processes of all kinds, of internal simulations of the mental processes of others, and of social phenomena such as shared understandings and collective actions. A variety of sample models – including ...

  2. Impact of Social Network and Business Model on Innovation Diffusion of Electric Vehicles in China

    Directory of Open Access Journals (Sweden)

    D. Y. Kong

    2014-01-01

    Full Text Available The diffusion of electric vehicles (EVs involves not only the technological development but also the construction of complex social networks. This paper uses the theory of network control to analyze the influence of network forms on EV diffusion in China, especially focusing on the building of EV business models (BMs and the resulting effects and control on the diffusion of EVs. The Bass model is adopted to forecast the diffusion process of EVs and genetic algorithm is used to estimate the parameters based on the diffusion data of Hybrid Electric Vehicle (HEV in the United States and Japan. Two different social network forms and BMs are selected, that is, battery leasing model and vehicle purchasing model, to analyze how different network forms may influence the innovation coefficient and imitation coefficient in the Bass model, which will in turn result in different diffusion results. Thereby, we can find the appropriate network forms and BMs for EVs which is suitable to the local market conditions.

  3. Model, Framework, and Platform of Health Persuasive Social Network

    Science.gov (United States)

    Al Ayubi, Soleh Udin

    2013-01-01

    Persuasive technology (PT) has the potential to support individuals to perform self-management and social support as a part of health behavior change. This has led a few researchers in the intersection of the areas of health behavior change and software engineering to apply behavior change and persuasion theories to software development practices,…

  4. Active influence in dynamical models of structural balance in social networks

    Science.gov (United States)

    Summers, Tyler H.; Shames, Iman

    2013-07-01

    We consider a nonlinear dynamical system on a signed graph, which can be interpreted as a mathematical model of social networks in which the links can have both positive and negative connotations. In accordance with a concept from social psychology called structural balance, the negative links play a key role in both the structure and dynamics of the network. Recent research has shown that in a nonlinear dynamical system modeling the time evolution of “friendliness levels” in the network, two opposing factions emerge from almost any initial condition. Here we study active external influence in this dynamical model and show that any agent in the network can achieve any desired structurally balanced state from any initial condition by perturbing its own local friendliness levels. Based on this result, we also introduce a new network centrality measure for signed networks. The results are illustrated in an international-relations network using United Nations voting record data from 1946 to 2008 to estimate friendliness levels amongst various countries.

  5. Next Generation Social Networks

    DEFF Research Database (Denmark)

    Sørensen, Lene Tolstrup; Skouby, Knud Erik

    2008-01-01

    When it comes to discussing the future of electronic communication, social networking is the buzzword. The Internet has become a platform where new social networks emerge and the Internet it itself support the more traditional computer supported communication. The way users build and verifies...... 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...

  6. In-House Communication Support System Based on the Information Propagation Model Utilizes Social Network

    Science.gov (United States)

    Takeuchi, Susumu; Teranishi, Yuuichi; Harumoto, Kaname; Shimojo, Shinji

    Almost all companies are now utilizing computer networks to support speedier and more effective in-house information-sharing and communication. However, existing systems are designed to support communications only within the same department. Therefore, in our research, we propose an in-house communication support system which is based on the “Information Propagation Model (IPM).” The IPM is proposed to realize word-of-mouth communication in a social network, and to support information-sharing on the network. By applying the system in a real company, we found that information could be exchanged between different and unrelated departments, and such exchanges of information could help to build new relationships between the users who are apart on the social network.

  7. A General Stochastic Information Diffusion Model in Social Networks Based on Epidemic Diseases

    Directory of Open Access Journals (Sweden)

    Hamidreza Sotoodeh

    2013-09-01

    Full Text Available Social networks are an important infrastructure forinformation, viruses and innovations propagation.Since users’behavior has influenced by other users’ activity, some groups of people would be made regard to similarity of users’interests. On the other hand, dealing with many events in real worlds, can be justified in social networks; spreadingdisease is one instance of them. People’s manner and infection severity are more important parameters in dissemination of diseases. Both of these reasons derive, whether the diffusion leads to an epidemic or not. SIRS is a hybrid model of SIR and SIS disease models to spread contamination. A person in this model can be returned tosusceptible state after it removed. According to communities which are established on the social network, we use thecompartmental type of SIRS model. During this paper, a general compartmental information diffusion model wouldbe proposed and extracted some of the beneficial parameters to analyze our model. To adapt our model to realistic behaviors, we use Mark ovian model, which would be helpful to create a stochastic manner of the proposed model.In the case of random model, we can calculate probabilities of transaction between states and predicting value of each state. The comparison between two mode of themodel shows that, the prediction of population would beverified in each state.

  8. Modeling Contagion Through Social Networks to Explain and Predict Gunshot Violence in Chicago, 2006 to 2014.

    Science.gov (United States)

    Green, Ben; Horel, Thibaut; Papachristos, Andrew V

    2017-03-01

    Every day in the United States, more than 200 people are murdered or assaulted with a firearm. Little research has considered the role of interpersonal ties in the pathways through which gun violence spreads. To evaluate the extent to which the people who will become subjects of gun violence can be predicted by modeling gun violence as an epidemic that is transmitted between individuals through social interactions. This study was an epidemiological analysis of a social network of individuals who were arrested during an 8-year period in Chicago, Illinois, with connections between people who were arrested together for the same offense. Modeling of the spread of gunshot violence over the network was assessed using a probabilistic contagion model that assumed individuals were subject to risks associated with being arrested together, in addition to demographic factors, such as age, sex, and neighborhood residence. Participants represented a network of 138 163 individuals who were arrested between January 1, 2006, and March 31, 2014 (29.9% of all individuals arrested in Chicago during this period), 9773 of whom were subjects of gun violence. Individuals were on average 27 years old at the midpoint of the study, predominantly male (82.0%) and black (75.6%), and often members of a gang (26.2%). Explanation and prediction of becoming a subject of gun violence (fatal or nonfatal) using epidemic models based on person-to-person transmission through a social network. Social contagion accounted for 63.1% of the 11 123 gunshot violence episodes; subjects of gun violence were shot on average 125 days after their infector (the person most responsible for exposing the subject to gunshot violence). Some subjects of gun violence were shot more than once. Models based on both social contagion and demographics performed best; when determining the 1.0% of people (n = 1382) considered at highest risk to be shot each day, the combined model identified 728 subjects of gun violence

  9. Analysis and models of bilateral investment treaties using a social networks approach

    Science.gov (United States)

    Saban, Daniela; Bonomo, Flavia; Stier-Moses, Nicolás E.

    2010-09-01

    Bilateral investment treaties (BITs) are agreements between two countries for the reciprocal encouragement, promotion and protection of investments in each other’s territories by companies based in either country. Germany and Pakistan signed the first BIT in 1959 and since then, BITs are one of the most popular and widespread form of international agreement. In this work we study the proliferation of BITs using a social networks approach. We propose a network growth model that dynamically replicates the empirical topological characteristics of the BIT network.

  10. A Hierarchy of Linear Threshold Models for the Spread of Political Revolutions on Social Networks

    CERN Document Server

    Lang, John C

    2015-01-01

    We study a linear threshold agent-based model (ABM) for the spread of political revolutions on social networks using empirical network data. We propose new techniques for building a hierarchy of simplified ordinary differential equation (ODE) based models that aim to capture essential features of the ABM, including effects of the actual networks, and give insight in the parameter regime transitions of the ABM. We relate the ABM and the hierarchy of models to a population-level compartmental ODE model that we proposed previously for the spread of political revolutions [1], which is shown to be mathematically consistent with the proposed ABM and provides a way to analyze the global behaviour of the ABM. This consistency with the linear threshold ABM also provides further justification a posteriori for the compartmental model of [1]. Extending concepts from epidemiological modelling, we define a basic reproduction number $R_0$ for the linear threshold ABM and apply it to predict ABM behaviour on empirical networ...

  11. 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…

  12. 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…

  13. 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.

  14. A two-stage broadcast message propagation model in social networks

    Science.gov (United States)

    Wang, Dan; Cheng, Shun-Jun

    2016-11-01

    Message propagation in social networks is becoming a popular topic in complex networks. One of the message types in social networks is called broadcast message. It refers to a type of message which has a unique and unknown destination for the publisher, such as 'lost and found'. Its propagation always has two stages. Due to this feature, rumor propagation model and epidemic propagation model have difficulty in describing this message's propagation accurately. In this paper, an improved two-stage susceptible-infected-removed model is proposed. We come up with the concept of the first forwarding probability and the second forwarding probability. Another part of our work is figuring out the influence to the successful message transmission chance in each level resulting from multiple reasons, including the topology of the network, the receiving probability, the first stage forwarding probability, the second stage forwarding probability as well as the length of the shortest path between the publisher and the relevant destination. The proposed model has been simulated on real networks and the results proved the model's effectiveness.

  15. Social network analysis

    OpenAIRE

    Mathias, Carlos Leonardo Kelmer

    2014-01-01

    In general, the paper develops a historiographical debate about the methodology of social network analysis. More than responding questions using such methodology, this article tries to introduce the historian to the founder bibliography of social network analysis. Since the publication of the famous article by John Barnes in 1954, sociologists linked to sociometric studies have usually employed the social network analysis in their studies. On the other hand, this methodology is not widespread...

  16. Marketing on social networks

    OpenAIRE

    Kadečková, Anna

    2016-01-01

    The bachelor´s thesis is focused on marketing communications on social networks in recruitment agency OPENN. The work is composed of three parts: literature review, own work and draft recommendations. The first part describes the basic concepts of marketing, marketing mix and communication mix, whose tools are used to successful marketing on social networks. Among other things, thesis informs on major social networks, including Facebook, Twitter, LinkedIn, Google+, YouTube and Instagram. It f...

  17. Detecting Rumors Through Modeling Information Propagation Networks in a Social Media Environment.

    Science.gov (United States)

    Liu, Yang; Xu, Songhua; Tourassi, Georgia

    2015-01-01

    In the midst of today's pervasive influence of social media content and activities, information credibility has increasingly become a major issue. Accordingly, identifying false information, e.g. rumors circulated in social media environments, attracts expanding research attention and growing interests. Many previous studies have exploited user-independent features for rumor detection. These prior investigations uniformly treat all users relevant to the propagation of a social media message as instances of a generic entity. Such a modeling approach usually adopts a homogeneous network to represent all users, the practice of which ignores the variety across an entire user population in a social media environment. Recognizing this limitation of modeling methodologies, this study explores user-specific features in a social media environment for rumor detection. The new approach hypothesizes that whether a user tends to spread a rumor is dependent upon specific attributes of the user in addition to content characteristics of the message itself. Under this hypothesis, information propagation patterns of rumors versus those of credible messages in a social media environment are systematically differentiable. To explore and exploit this hypothesis, we develop a new information propagation model based on a heterogeneous user representation for rumor recognition. The new approach is capable of differentiating rumors from credible messages through observing distinctions in their respective propagation patterns in social media. Experimental results show that the new information propagation model based on heterogeneous user representation can effectively distinguish rumors from credible social media content.

  18. Spatially embedded social networks: dynamic models and data reconstruction

    OpenAIRE

    Hegemann, Rachel Anne

    2012-01-01

    ``Bottom-up" and ``top-down" identify two fundamental approaches to modeling complex systems. As the name suggests, a bottom-up approach analyzes how elements on a micro scale affect observations on the macro scale. On the other hand, top-down approaches use macro scale data to identify patterns evolved from the micro scale. This thesis details two models, agent-based and data driven, designed for complex systems. These models are applied to the complex system of street gang violence. The fir...

  19. A Privacy Preservation Model for Health-Related Social Networking Sites.

    Science.gov (United States)

    Li, Jingquan

    2015-07-08

    The increasing use of social networking sites (SNS) in health care has resulted in a growing number of individuals posting personal health information online. These sites may disclose users' health information to many different individuals and organizations and mine it for a variety of commercial and research purposes, yet the revelation of personal health information to unauthorized individuals or entities brings a concomitant concern of greater risk for loss of privacy among users. Many users join multiple social networks for different purposes and enter personal and other specific information covering social, professional, and health domains into other websites. Integration of multiple online and real social networks makes the users vulnerable to unintentional and intentional security threats and misuse. This paper analyzes the privacy and security characteristics of leading health-related SNS. It presents a threat model and identifies the most important threats to users and SNS providers. Building on threat analysis and modeling, this paper presents a privacy preservation model that incorporates individual self-protection and privacy-by-design approaches and uses the model to develop principles and countermeasures to protect user privacy. This study paves the way for analysis and design of privacy-preserving mechanisms on health-related SNS.

  20. A Privacy Preservation Model for Health-Related Social Networking Sites

    Science.gov (United States)

    2015-01-01

    The increasing use of social networking sites (SNS) in health care has resulted in a growing number of individuals posting personal health information online. These sites may disclose users' health information to many different individuals and organizations and mine it for a variety of commercial and research purposes, yet the revelation of personal health information to unauthorized individuals or entities brings a concomitant concern of greater risk for loss of privacy among users. Many users join multiple social networks for different purposes and enter personal and other specific information covering social, professional, and health domains into other websites. Integration of multiple online and real social networks makes the users vulnerable to unintentional and intentional security threats and misuse. This paper analyzes the privacy and security characteristics of leading health-related SNS. It presents a threat model and identifies the most important threats to users and SNS providers. Building on threat analysis and modeling, this paper presents a privacy preservation model that incorporates individual self-protection and privacy-by-design approaches and uses the model to develop principles and countermeasures to protect user privacy. This study paves the way for analysis and design of privacy-preserving mechanisms on health-related SNS. PMID:26155953

  1. Trust and Partner Selection in Social Networks: An Experimentally Grounded Model

    CERN Document Server

    Boero, Riccardo; Squazzoni, Flaminio

    2010-01-01

    This paper presents an experimentally grounded model on the relevance of partner selection for the emergence of trust and cooperation among individuals. By combining experimental evidence and network simulation, our model investigates the link of interaction outcome and social structure formation and shows that dynamic networks lead to positive outcomes when cooperators have the capability of creating more links and isolating free-riders. By emphasizing the self-reinforcing dynamics of interaction outcome and structure formation, our results cast the argument about the relevance of interaction continuity for cooperation in new light and provide insights to guide the design of new lab experiments.

  2. Modeling Social Networks with Node Attributes using the Multiplicative Attribute Graph Model

    Science.gov (United States)

    2011-06-24

    technological and natural domains exhibit rich connectiv - ity patterns and nodes in such networks are often labeled with attributes or features. We...world networks demonstrate that the MAG model reliably captures the network connectiv - ity patterns and outperforms present state-of-the-art methods

  3. Line graphs as social networks

    CERN Document Server

    Krawczyk, Malgorzata; Mańka-Krasoń, Anna; Kułakowski, Krzysztof

    2010-01-01

    The line graphs are clustered and assortative. They share these topological features with some social networks. We argue that this similarity reveals the cliquey character of the social networks. In the model proposed here, a social network is the line graph of an initial network of families, communities, interest groups, school classes and small companies. These groups play the role of nodes, and individuals are represented by links between these nodes. The picture is supported by the data on the LiveJournal network of about 8 x 10^6 people. In particular, sharp maxima of the observed data of the degree dependence of the clustering coefficient C(k) are associated with cliques in the social network.

  4. A novel game theoretic approach for modeling competitive information diffusion in social networks with heterogeneous nodes

    Science.gov (United States)

    Agha Mohammad Ali Kermani, Mehrdad; Fatemi Ardestani, Seyed Farshad; Aliahmadi, Alireza; Barzinpour, Farnaz

    2017-01-01

    Influence maximization deals with identification of the most influential nodes in a social network given an influence model. In this paper, a game theoretic framework is developed that models a competitive influence maximization problem. A novel competitive influence model is additionally proposed that incorporates user heterogeneity, message content, and network structure. The proposed game-theoretic model is solved using Nash Equilibrium in a real-world dataset. It is shown that none of the well-known strategies are stable and at least one player has the incentive to deviate from the proposed strategy. Moreover, violation of Nash equilibrium strategy by each player leads to their reduced payoff. Contrary to previous works, our results demonstrate that graph topology, as well as the nodes' sociability and initial tendency measures have an effect on the determination of the influential node in the network.

  5. The data-driven null models for information dissemination tree in social networks

    Science.gov (United States)

    Zhang, Zhiwei; Wang, Zhenyu

    2017-10-01

    For the purpose of detecting relatedness and co-occurrence between users, as well as the distribution features of nodes in spreading path of a social network, this paper explores topological characteristics of information dissemination trees (IDT) that can be employed indirectly to probe the information dissemination laws within social networks. Hence, three different null models of IDT are presented in this article, including the statistical-constrained 0-order IDT null model, the random-rewire-broken-edge 0-order IDT null model and the random-rewire-broken-edge 2-order IDT null model. These null models firstly generate the corresponding randomized copy of an actual IDT; then the extended significance profile, which is developed by adding the cascade ratio of information dissemination path, is exploited not only to evaluate degree correlation of two nodes associated with an edge, but also to assess the cascade ratio of different length of information dissemination paths. The experimental correspondences of the empirical analysis for several SinaWeibo IDTs and Twitter IDTs indicate that the IDT null models presented in this paper perform well in terms of degree correlation of nodes and dissemination path cascade ratio, which can be better to reveal the features of information dissemination and to fit the situation of real social networks.

  6. Privacy in Social Networks

    CERN Document Server

    Zheleva, Elena

    2012-01-01

    This synthesis lecture provides a survey of work on privacy in online social networks (OSNs). This work encompasses concerns of users as well as service providers and third parties. Our goal is to approach such concerns from a computer-science perspective, and building upon existing work on privacy, security, statistical modeling and databases to provide an overview of the technical and algorithmic issues related to privacy in OSNs. We start our survey by introducing a simple OSN data model and describe common statistical-inference techniques that can be used to infer potentially sensitive inf

  7. An Evolutionary Game Model of Multi-Topics Diffusion in Social Network

    Directory of Open Access Journals (Sweden)

    Su Jia-Hao

    2017-01-01

    Full Text Available One major function of social networks is the dissemination of information such as news, comments, and rumors. The information passing from a sender to a receiver intrinsically involves both of them by considering their memory, reputation, and preference, which further determine their decisions of whether or not to diffuse the topic. To understand such human aspects of the topics dissemination, we propose a game theoretical model of the multi-topics diffusion mechanisms in a social network. Each individual in the network is considered as both sender and receiver, who transmits different topics taking into account their payoffs and personalities (including memories, reputation and preferences. Several cases were analyzed, and the results suggest that multi-topics dissemination is strongly affected by self-perceived, gregarious and information gain.

  8. Social inheritance can explain the structure of animal social networks.

    Science.gov (United States)

    Ilany, Amiyaal; Akçay, Erol

    2016-06-28

    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.

  9. 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

  10. Bass-SIR model for diffusion of new products in social networks.

    Science.gov (United States)

    Fibich, Gadi

    2016-09-01

    We consider the diffusion of new products in social networks, where consumers who adopt the product can later "recover" and stop influencing others to adopt the product. We show that the diffusion is not described by the susceptible-infected-recovered (SIR) model, but rather by a new model, the Bass-SIR model, which combines the Bass model for diffusion of new products with the SIR model for epidemics. The phase transition of consumers from nonadopters to adopters is described by a nonstandard Kolmogorov-Johnson-Mehl-Avrami model, in which clusters growth is limited by adopters' recovery. Therefore, diffusion in the Bass-SIR model only depends on the local structure of the social network, but not on the average distance between consumers. Consequently, unlike the SIR model, a small-worlds structure has a negligible effect on the diffusion. Moreover, unlike the SIR model, there is no threshold value above which the diffusion will peter out. Surprisingly, diffusion on scale-free networks is nearly identical to that on Cartesian ones.

  11. Bass-SIR model for diffusion of new products in social networks

    Science.gov (United States)

    Fibich, Gadi

    2016-09-01

    We consider the diffusion of new products in social networks, where consumers who adopt the product can later "recover" and stop influencing others to adopt the product. We show that the diffusion is not described by the susceptible-infected-recovered (SIR) model, but rather by a new model, the Bass-SIR model, which combines the Bass model for diffusion of new products with the SIR model for epidemics. The phase transition of consumers from nonadopters to adopters is described by a nonstandard Kolmogorov-Johnson-Mehl-Avrami model, in which clusters growth is limited by adopters' recovery. Therefore, diffusion in the Bass-SIR model only depends on the local structure of the social network, but not on the average distance between consumers. Consequently, unlike the SIR model, a small-worlds structure has a negligible effect on the diffusion. Moreover, unlike the SIR model, there is no threshold value above which the diffusion will peter out. Surprisingly, diffusion on scale-free networks is nearly identical to that on Cartesian ones.

  12. Dynamic Trust Models between Users over Social Networks

    Science.gov (United States)

    2016-03-30

    model, we consider introducing some trust discount factors. The simplest one is an exponential discount factor defined by ρ(Δt; λ) = exp(−λΔt), where...the Cosmetics review dataset. The other one is composed of review records collected from “anikore”, a ranking and review site for anime , which is...referred to as the Anime review dataset. In both the datasets, each record has 4-triple (u, i, s, t), which means user u gives a score s to item i at

  13. The Social Networking Application Success Model: An Empirical Study of Facebook and Twitter

    Directory of Open Access Journals (Sweden)

    Carol X. J. Ou

    2016-06-01

    Full Text Available Social networking applications (SNAs are among the fastest growing web applications of recent years. In this paper, we propose a causal model to assess the success of SNAs, grounded on DeLone and McLean’s updated information systems (IS success model. In addition to their original three dimensions of quality, i.e., system quality, information quality and service quality, we propose that a fourth dimension - networking quality - contributes to SNA success. We empirically examined the proposed research model with a survey of 168 Facebook and 149 Twitter users. The data validates the significant role of networking quality in determining the focal SNA’s success. The theoretical and practical implications are discussed.

  14. Reliability and efficiency of generalized rumor spreading model on complex social networks

    CERN Document Server

    Naimi, Yaghoob

    2013-01-01

    We introduce the generalized rumor spreading model and investigate some properties of this model on different complex social networks. Despite pervious rumor models that both the spreader-spreader ($SS$) and the spreader-stifler ($SR$) interactions have the same rate $\\alpha$, we define $\\alpha^{(1)}$ and $\\alpha^{(2)}$ for $SS$ and $SR$ interactions, respectively. The effect of variation of $\\alpha^{(1)}$ and $\\alpha^{(2)}$ on the final density of stiflers is investigated. Furthermore, the influence of the topological structure of the network in rumor spreading is studied by analyzing the behavior of several global parameters such as reliability and efficiency. Our results show that while networks with homogeneous connectivity patterns reach a higher reliability, scale-free topologies need a less time to reach a steady state with respect the rumor.

  15. Reliability and Efficiency of Generalized Rumor Spreading Model on Complex Social Networks

    Institute of Scientific and Technical Information of China (English)

    Yaghoob Naimi; Mohammad Naimi

    2013-01-01

    We introduce the generalized rumor spreading model and investigate some properties of this model on different complex social networks.Despite pervious rumor models that both the spreader-spreader (SS) and the spreaderstifler (SR) interactions have the same rate α,we define α(1) and α(2) for SS and SR interactions,respectively.The effect of variation of α(1) and α(2) on the final density of stiflers is investigated.Furthermore,the influence of the topological structure of the network in rumor spreading is studied by analyzing the behavior of several global parameters such as reliability and efficiency.Our results show that while networks with homogeneous connectivity patterns reach a higher reliability,scale-free topologies need a less time to reach a steady state with respect the rumor.

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

    Directory of Open Access Journals (Sweden)

    Jundong Chen

    2014-05-01

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

  17. 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.

  18. A stochastic agent-based model of pathogen propagation in dynamic multi-relational social networks

    Science.gov (United States)

    Khan, Bilal; Dombrowski, Kirk; Saad, Mohamed

    2015-01-01

    We describe a general framework for modeling and stochastic simulation of epidemics in realistic dynamic social networks, which incorporates heterogeneity in the types of individuals, types of interconnecting risk-bearing relationships, and types of pathogens transmitted across them. Dynamism is supported through arrival and departure processes, continuous restructuring of risk relationships, and changes to pathogen infectiousness, as mandated by natural history; dynamism is regulated through constraints on the local agency of individual nodes and their risk behaviors, while simulation trajectories are validated using system-wide metrics. To illustrate its utility, we present a case study that applies the proposed framework towards a simulation of HIV in artificial networks of intravenous drug users (IDUs) modeled using data collected in the Social Factors for HIV Risk survey. PMID:25859056

  19. Hoodsquare: Modeling and Recommending Neighborhoods in Location-based Social Networks

    CERN Document Server

    Zhang, Amy X; Scellato, Salvatore; Mascolo, Cecilia

    2013-01-01

    Information garnered from activity on location-based social networks can be harnessed to characterize urban spaces and organize them into neighborhoods. In this work, we adopt a data-driven approach to the identification and modeling of urban neighborhoods using location-based social networks. We represent geographic points in the city using spatio-temporal information about Foursquare user check-ins and semantic information about places, with the goal of developing features to input into a novel neighborhood detection algorithm. The algorithm first employs a similarity metric that assesses the homogeneity of a geographic area, and then with a simple mechanism of geographic navigation, it detects the boundaries of a city's neighborhoods. The models and algorithms devised are subsequently integrated into a publicly available, map-based tool named Hoodsquare that allows users to explore activities and neighborhoods in cities around the world. Finally, we evaluate Hoodsquare in the context of a recommendation ap...

  20. Influence analysis of information erupted on social networks based on SIR model

    Science.gov (United States)

    Zhou, Xue; Hu, Yong; Wu, Yue; Xiong, Xi

    2015-07-01

    In this paper, according to the similarity of chain reaction principle and the characteristics of information propagation on social network, we proposed a new word "information bomb". Based on the complex networks and SIR model, dynamical evolution equations were setup. Then methods used to evaluate the four indexes of bomb power were given, including influence breadth, influence strength, peak time and relaxation time. At last, the power of information was ascertained through these indexes. The process of information propagation is simulated to illustrate the spreading characteristics through the results. Then parameters which impact on the power of information bomb are analyzed and some methods which control the propagation of information are given.

  1. Social insect colony as a biological regulatory system: modelling information flow in dominance networks.

    Science.gov (United States)

    Nandi, Anjan K; Sumana, Annagiri; Bhattacharya, Kunal

    2014-12-06

    Social insects provide an excellent platform to investigate flow of information in regulatory systems since their successful social organization is essentially achieved by effective information transfer through complex connectivity patterns among the colony members. Network representation of such behavioural interactions offers a powerful tool for structural as well as dynamical analysis of the underlying regulatory systems. In this paper, we focus on the dominance interaction networks in the tropical social wasp Ropalidia marginata-a species where behavioural observations indicate that such interactions are principally responsible for the transfer of information between individuals about their colony needs, resulting in a regulation of their own activities. Our research reveals that the dominance networks of R. marginata are structurally similar to a class of naturally evolved information processing networks, a fact confirmed also by the predominance of a specific substructure-the 'feed-forward loop'-a key functional component in many other information transfer networks. The dynamical analysis through Boolean modelling confirms that the networks are sufficiently stable under small fluctuations and yet capable of more efficient information transfer compared to their randomized counterparts. Our results suggest the involvement of a common structural design principle in different biological regulatory systems and a possible similarity with respect to the effect of selection on the organization levels of such systems. The findings are also consistent with the hypothesis that dominance behaviour has been shaped by natural selection to co-opt the information transfer process in such social insect species, in addition to its primal function of mediation of reproductive competition in the colony.

  2. Line graphs as social networks

    Science.gov (United States)

    Krawczyk, M. J.; Muchnik, L.; Mańka-Krasoń, A.; Kułakowski, K.

    2011-07-01

    It was demonstrated recently that the line graphs are clustered and assortative. These topological features are known to characterize some social networks [M.E.J. Newman, Y. Park, Why social networks are different from other types of networks, Phys. Rev. E 68 (2003) 036122]; it was argued that this similarity reveals their cliquey character. In the model proposed here, a social network is the line graph of an initial network of families, communities, interest groups, school classes and small companies. These groups play the role of nodes, and individuals are represented by links between these nodes. The picture is supported by the data on the LiveJournal network of about 8×10 6 people.

  3. 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

  4. Reconstruction of a real world social network using the Potts model and Loopy Belief Propagation

    Directory of Open Access Journals (Sweden)

    Cristian eBisconti

    2015-11-01

    Full Text Available The scope of this paper is to test the adoption of a statistical model derived from Condensed Matter Physics, aiming at the reconstruction of a networked structure from observations of the states of the nodes in the network.The inverse Potts model, normally applied to observations of quantum states, is here addressed to observations of the node states in a network and their (anticorrelations, thus inferring interactions as links connecting the nodes. Adopting the Bethe approximation, such an inverse problem is known to be tractable.Within this operational framework, we discuss and apply this network-reconstruction method to a small real-world social network, where it is easy to track statuses of its members: the Italian parliament, adopted as a case study. The dataset is made of (cosponsorships of law proposals by parliament members. In previous studies of similar activity-based networks, the graph structure was inferred directly from activity co-occurrences: here we compare our statistical reconstruction with standard methods, outlining discrepancies and advantages.

  5. Predicting future conflict between team-members with parameter-free models of social networks

    Science.gov (United States)

    Rovira-Asenjo, Núria; Gumí, Tània; Sales-Pardo, Marta; Guimerà, Roger

    2013-06-01

    Despite the well-documented benefits of working in teams, teamwork also results in communication, coordination and management costs, and may lead to personal conflict between team members. In a context where teams play an increasingly important role, it is of major importance to understand conflict and to develop diagnostic tools to avert it. Here, we investigate empirically whether it is possible to quantitatively predict future conflict in small teams using parameter-free models of social network structure. We analyze data of conflict appearance and resolution between 86 team members in 16 small teams, all working in a real project for nine consecutive months. We find that group-based models of complex networks successfully anticipate conflict in small teams whereas micro-based models of structural balance, which have been traditionally used to model conflict, do not.

  6. Predicting future conflict between team-members with parameter-free models of social networks

    CERN Document Server

    Rovira-Asenjo, Nuria; Sales-Pardo, Marta; Guimera, Roger

    2014-01-01

    Despite the well-documented benefits of working in teams, teamwork also results in communication, coordination and management costs, and may lead to personal conflict between team members. In a context where teams play an increasingly important role, it is of major importance to understand conflict and to develop diagnostic tools to avert it. Here, we investigate empirically whether it is possible to quantitatively predict future conflict in small teams using parameter-free models of social network structure. We analyze data of conflict appearance and resolution between 86 team members in 16 small teams, all working in a real project for nine consecutive months. We find that group-based models of complex networks successfully anticipate conflict in small teams whereas micro-based models of structural balance, which have been traditionally used to model conflict, do not.

  7. Predicting future conflict between team-members with parameter-free models of social networks.

    Science.gov (United States)

    Rovira-Asenjo, Núria; Gumí, Tània; Sales-Pardo, Marta; Guimerà, Roger

    2013-01-01

    Despite the well-documented benefits of working in teams, teamwork also results in communication, coordination and management costs, and may lead to personal conflict between team members. In a context where teams play an increasingly important role, it is of major importance to understand conflict and to develop diagnostic tools to avert it. Here, we investigate empirically whether it is possible to quantitatively predict future conflict in small teams using parameter-free models of social network structure. We analyze data of conflict appearance and resolution between 86 team members in 16 small teams, all working in a real project for nine consecutive months. We find that group-based models of complex networks successfully anticipate conflict in small teams whereas micro-based models of structural balance, which have been traditionally used to model conflict, do not.

  8. Using the relational event model (REM) to investigate the temporal dynamics of animal social networks.

    Science.gov (United States)

    Tranmer, Mark; Marcum, Christopher Steven; Morton, F Blake; Croft, Darren P; de Kort, Selvino R

    2015-03-01

    Social dynamics are of fundamental importance in animal societies. Studies on nonhuman animal social systems often aggregate social interaction event data into a single network within a particular time frame. Analysis of the resulting network can provide a useful insight into the overall extent of interaction. However, through aggregation, information is lost about the order in which interactions occurred, and hence the sequences of actions over time. Many research hypotheses relate directly to the sequence of actions, such as the recency or rate of action, rather than to their overall volume or presence. Here, we demonstrate how the temporal structure of social interaction sequences can be quantified from disaggregated event data using the relational event model (REM). We first outline the REM, explaining why it is different from other models for longitudinal data, and how it can be used to model sequences of events unfolding in a network. We then discuss a case study on the European jackdaw, Corvus monedula, in which temporal patterns of persistence and reciprocity of action are of interest, and present and discuss the results of a REM analysis of these data. One of the strengths of a REM analysis is its ability to take into account different ways in which data are collected. Having explained how to take into account the way in which the data were collected for the jackdaw study, we briefly discuss the application of the model to other studies. We provide details of how the models may be fitted in the R statistical software environment and outline some recent extensions to the REM framework.

  9. Modeling of information diffusion in Twitter-like social networks under information overload.

    Science.gov (United States)

    Li, Pei; Li, Wei; Wang, Hui; Zhang, Xin

    2014-01-01

    Due to the existence of information overload in social networks, it becomes increasingly difficult for users to find useful information according to their interests. This paper takes Twitter-like social networks into account and proposes models to characterize the process of information diffusion under information overload. Users are classified into different types according to their in-degrees and out-degrees, and user behaviors are generalized into two categories: generating and forwarding. View scope is introduced to model the user information-processing capability under information overload, and the average number of times a message appears in view scopes after it is generated by a given type user is adopted to characterize the information diffusion efficiency, which is calculated theoretically. To verify the accuracy of theoretical analysis results, we conduct simulations and provide the simulation results, which are consistent with the theoretical analysis results perfectly. These results are of importance to understand the diffusion dynamics in social networks, and this analysis framework can be extended to consider more realistic situations.

  10. Reconstruction of a Real World Social Network using the Potts Model and Loopy Belief Propagation.

    Science.gov (United States)

    Bisconti, Cristian; Corallo, Angelo; Fortunato, Laura; Gentile, Antonio A; Massafra, Andrea; Pellè, Piergiuseppe

    2015-01-01

    The scope of this paper is to test the adoption of a statistical model derived from Condensed Matter Physics, for the reconstruction of the structure of a social network. The inverse Potts model, traditionally applied to recursive observations of quantum states in an ensemble of particles, is here addressed to observations of the members' states in an organization and their (anti)correlations, thus inferring interactions as links among the members. Adopting proper (Bethe) approximations, such an inverse problem is showed to be tractable. Within an operational framework, this network-reconstruction method is tested for a small real-world social network, the Italian parliament. In this study case, it is easy to track statuses of the parliament members, using (co)sponsorships of law proposals as the initial dataset. In previous studies of similar activity-based networks, the graph structure was inferred directly from activity co-occurrences: here we compare our statistical reconstruction with such standard methods, outlining discrepancies and advantages.

  11. Vaccines, Contagion, and Social Networks

    CERN Document Server

    Ogburn, Elizabeth L

    2014-01-01

    Consider the causal effect that one individual's treatment may have on another individual's outcome when the outcome is contagious, with specific application to the effect of vaccination on an infectious disease outcome. The effect of one individual's vaccination on another's outcome can be decomposed into two different causal effects, called the "infectiousness" and "contagion" effects. We present identifying assumptions and estimation or testing procedures for infectiousness and contagion effects in two different settings: (1) using data sampled from independent groups of observations, and (2) using data collected from a single interdependent social network. The methods that we propose for social network data require fitting generalized linear models (GLMs). GLMs and other statistical models that require independence across subjects have been used widely to estimate causal effects in social network data, but, because the subjects in networks are presumably not independent, the use of such models is generall...

  12. Learning from Your Network of Friends: A Trajectory Representation Learning Model Based on Online Social Ties

    KAUST Repository

    Alharbi, Basma Mohammed

    2017-02-07

    Location-Based Social Networks (LBSNs) capture individuals whereabouts for a large portion of the population. To utilize this data for user (location)-similarity based tasks, one must map the raw data into a low-dimensional uniform feature space. However, due to the nature of LBSNs, many users have sparse and incomplete check-ins. In this work, we propose to overcome this issue by leveraging the network of friends, when learning the new feature space. We first analyze the impact of friends on individuals\\'s mobility, and show that individuals trajectories are correlated with thoseof their friends and friends of friends (2-hop friends) in an online setting. Based on our observation, we propose a mixed-membership model that infers global mobility patterns from users\\' check-ins and their network of friends, without impairing the model\\'s complexity. Our proposed model infers global patterns and learns new representations for both usersand locations simultaneously. We evaluate the inferred patterns and compare the quality of the new user representation against baseline methods on a social link prediction problem.

  13. A mathematical modeling technique with network flows for social welfare maximization in deregulated electricity markets

    Directory of Open Access Journals (Sweden)

    Ryo Hase

    2016-01-01

    Full Text Available This paper presents a sequential solution method to discover efficient trades in an electricity market model. The market model represents deregulated electricity market consisting of four types of participants: independent power producers, retailers, public utilities, and consumers. Our model is based on graph theory, and the market participants are denoted by a network composes of three types of agents including sellers, buyers, and traders. The market participants have different capacity and demand of electricity from each other, and each electricity trade should satisfy the capacity and demand. Our sequential solution method can discover efficient electricity trades satisfying the constraints regarding capacity and demand by utilizing network flow. Simulation results demonstrate the efficiency of electricity trades determined by our method by examining social welfare, which is the total of payoffs of all market participants. Furthermore, the simulation results also indicate the allocation of payoff to each market participant.

  14. [Methodological novelties applied to the anthropology of food: agent-based models and social networks analysis].

    Science.gov (United States)

    Díaz Córdova, Diego

    2016-01-01

    The aim of this article is to introduce two methodological strategies that have not often been utilized in the anthropology of food: agent-based models and social networks analysis. In order to illustrate these methods in action, two cases based in materials typical of the anthropology of food are presented. For the first strategy, fieldwork carried out in Quebrada de Humahuaca (province of Jujuy, Argentina) regarding meal recall was used, and for the second, elements of the concept of "domestic consumption strategies" applied by Aguirre were employed. The underlying idea is that, given that eating is recognized as a "total social fact" and, therefore, as a complex phenomenon, the methodological approach must also be characterized by complexity. The greater the number of methods utilized (with the appropriate rigor), the better able we will be to understand the dynamics of feeding in the social environment.

  15. Analysis of Infectious-Recovery Epidemic Models for Membership Dynamics of Online Social Networks

    CERN Document Server

    Cooney, Daniel; Bar-Yam, Yaneer

    2016-01-01

    The recent rapid growth of social media and online social networks (OSNs) has raised interesting questions about the spread of ideas and fads within our society. In the past year, several papers have drawn analogies between the rise and fall in popularity of OSNs and mathematical models used to study infectious disease. One such model, the irSIR model, made use of the idea of "infectious recovery" to outperform the traditional SIR model in replicating the rise and fall of MySpace and to predict a rapid drop in the popularity of Facebook. Here we explore the irSIR model and two of its logical extensions and we mathematically characterize the initial and long-run behavior of these dynamical systems. In particular, while the original irSIR model always predicts extinction of a social epidemic, we construct an extension of the model that matches the exponential growth phase of the irSIR model while allowing for the possibility of an arbitrary proportion of infections in the long run.

  16. A Firm-Growing Model and the Study of Communication Patterns' Effect on the Structure of Firm's Social Network

    Science.gov (United States)

    Chen, Liang; Li, Haigang; Chen, Zhong; Li, Li; He, Da-Ren

    In this article, we propose a firm-growing model, and then collect empirical data to test model validity. The simulation results agree well with the empirical data. We next explore the effect of communication patterns on the growth and structure of firm’s social network and find that the extents to which employees reluctantly interact within or across departments significantly influence the structure of firm’s social network.

  17. Engineering online and in-person social networks to sustain physical activity: application of a conceptual model.

    Science.gov (United States)

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

    2013-08-14

    High rates of physical inactivity compromise the health status of populations globally. Social networks have been shown to influence physical activity (PA), but little is known about how best to engineer social networks to sustain PA. To improve procedures for building networks that shape PA as a normative behavior, there is a need for more specific hypotheses about how social variables influence PA. There is also a need to integrate concepts from network science with ecological concepts that often guide the design of in-person and electronically-mediated interventions. Therefore, this paper: (1) proposes a conceptual model that integrates principles from network science and ecology across in-person and electronically-mediated intervention modes; and (2) illustrates the application of this model to the design and evaluation of a social network intervention for PA. A conceptual model for engineering social networks was developed based on a scoping literature review of modifiable social influences on PA. The model guided the design of a cluster randomized controlled trial in which 308 sedentary adults were randomly assigned to three groups: WalkLink+: prompted and provided feedback on participants' online and in-person social-network interactions to expand networks for PA, plus provided evidence-based online walking program and weekly walking tips; WalkLink: evidence-based online walking program and weekly tips only; Minimal Treatment Control: weekly tips only. The effects of these treatment conditions were assessed at baseline, post-program, and 6-month follow-up. The primary outcome was accelerometer-measured PA. Secondary outcomes included objectively-measured aerobic fitness, body mass index, waist circumference, blood pressure, and neighborhood walkability; and self-reported measures of the physical environment, social network environment, and social network interactions. The differential effects of the three treatment conditions on primary and secondary

  18. Security Visualization Analytics Model in Online Social Networks Using Data Mining and Graph-based Structure Algorithms

    Directory of Open Access Journals (Sweden)

    Prajit Limsaiprom

    2014-07-01

    Full Text Available The rise of the Internet accelerates the creation of various large-scale online social networks, which can be described the relationships and activities between human beings. The online social networks relationships in real world are too big to present with useful information to identify the criminal or cyber-attacks. This research proposed new information security analytic model for online social networks, which called Security Visualization Analytics (SVA Model. SVA Model used the set of algorithms (1 Graph-based Structure algorithm to analyze the key factors of influencing nodes about density, centrality and the cohesive subgroup to identify the influencing nodes of anomaly and attack patterns (2 Supervised Learning with oneR classification algorithm was used to predict new links from such influencing nodes in online social networks on discovering surprising links in the existing ones of influencing nodes, which nodes in online social networks will be linked next from the attacked influencing nodes to monitor the risk. The results showed 42 influencing nodes of anomaly and attack patterns and can be predict 31 new links from such nodes were achieved by SVA Model with the accuracy of confidence level 95.0%. The new proposed model and results illustrated SVA Model was significance analysis. Such understanding can lead to efficient implementation of tools to links prediction in online social networks. They could be applied as a guide to further investigate of social networks behavior to improve the security model and notify the risk, computer viruses or cyber-attacks for online social networks in advance.

  19. Social network analysis

    NARCIS (Netherlands)

    W. de Nooy

    2009-01-01

    Social network analysis (SNA) focuses on the structure of ties within a set of social actors, e.g., persons, groups, organizations, and nations, or the products of human activity or cognition such as web sites, semantic concepts, and so on. It is linked to structuralism in sociology stressing the si

  20. 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.

  1. Rumor-Propagation Model with Consideration of Refutation Mechanism in Homogeneous Social Networks

    Directory of Open Access Journals (Sweden)

    Laijun Zhao

    2014-01-01

    Full Text Available In recent years, increasing attention has been paid to how to effectively manage rumor propagation. Based on previous studies of rumor propagation and some strategies used by the authorities to refute rumors and manage rumor propagation, we develop a new rumor-propagation model with consideration of refutation mechanism. In this paper, we describe the dynamic process of rumor propagation by accounting for the refutation mechanism in homogeneous social networks. And then, we derive mean-field equations for rumor-propagation process. We then analyze the stability of the model with respect to changes in parameter values. Our results show that there exists a critical threshold λc that is inversely proportional to the average degree of the social networks and is positively correlated with the strength of the refutation mechanism. If the spreading rate is bigger than the critical threshold λc, rumors can be spread. Our numerical simulations in homogeneous networks demonstrate that increasing the ignorant’s refutation rate β can reduce the peak value of spreaders density, which is better than increasing the spreader’s refutation rate η. Therefore, based on the seriousness of the rumor propagation and the rumor-propagation rate, the authorities can choose effective strategies that increase the refutation rate so that they can reduce the maximum influence of the rumor.

  2. Social contagions on weighted networks

    Science.gov (United States)

    Zhu, Yu-Xiao; Wang, Wei; Tang, Ming; Ahn, Yong-Yeol

    2017-07-01

    We investigate critical behaviors of a social contagion model on weighted networks. An edge-weight compartmental approach is applied to analyze the weighted social contagion on strongly heterogenous networks with skewed degree and weight distributions. We find that degree heterogeneity cannot only alter the nature of contagion transition from discontinuous to continuous but also can enhance or hamper the size of adoption, depending on the unit transmission probability. We also show that the heterogeneity of weight distribution always hinders social contagions, and does not alter the transition type.

  3. Social contagions on weighted networks

    CERN Document Server

    Zhu, Yu-Xiao; Tang, Ming; Ahn, Yong-Yeol

    2016-01-01

    We investigate critical behaviors of a social contagion model on weighted networks. An edge-weight compartmental approach is applied to analyze the weighted social contagion on strongly heterogenous networks with skewed degree and weight distributions. We find that degree heterogeneity can not only alter the nature of contagion transition from discontinuous to continuous but also can enhance or hamper the size of adoption, depending on the unit transmission probability. We also show that, the heterogeneity of weight distribution always hinder social contagions, and does not alter the transition type.

  4. Retrieving quantifiable social media data from human sensor networks for disaster modeling and crisis mapping

    Science.gov (United States)

    Aulov, Oleg

    This dissertation presents a novel approach that utilizes quantifiable social media data as a human aware, near real-time observing system, coupled with geophysical predictive models for improved response to disasters and extreme events. It shows that social media data has the potential to significantly improve disaster management beyond informing the public, and emphasizes the importance of different roles that social media can play in management, monitoring, modeling and mitigation of natural and human-caused extreme disasters. In the proposed approach Social Media users are viewed as "human sensors" that are "deployed" in the field, and their posts are considered to be "sensor observations", thus different social media outlets all together form a Human Sensor Network. We utilized the "human sensor" observations, as boundary value forcings, to show improved geophysical model forecasts of extreme disaster events when combined with other scientific data such as satellite observations and sensor measurements. Several recent extreme disasters are presented as use case scenarios. In the case of the Deepwater Horizon oil spill disaster of 2010 that devastated the Gulf of Mexico, the research demonstrates how social media data from Flickr can be used as a boundary forcing condition of GNOME oil spill plume forecast model, and results in an order of magnitude forecast improvement. In the case of Hurricane Sandy NY/NJ landfall impact of 2012, we demonstrate how the model forecasts, when combined with social media data in a single framework, can be used for near real-time forecast validation, damage assessment and disaster management. Owing to inherent uncertainties in the weather forecasts, the NOAA operational surge model only forecasts the worst-case scenario for flooding from any given hurricane. Geolocated and time-stamped Instagram photos and tweets allow near real-time assessment of the surge levels at different locations, which can validate model forecasts, give

  5. An Introduction to Models of Online Peer-to-Peer Social Networking

    CERN Document Server

    Kesidis, George

    2010-01-01

    This book concerns peer-to-peer applications and mechanisms operating on the Internet, particularly those that are not fully automated and involve significant human interaction. So, the realm of interest is the intersection of distributed systems and online social networking. Generally, simple models are described to clarify the ideas. Beginning with short overviews of caching, graph theory and game theory, we cover the basic ideas of structured and unstructured search. We then describe a simple framework for reputations and for iterated referrals and consensus. This framework is applied to a

  6. Online Advertising in Social Networks

    Science.gov (United States)

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

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

  7. Modelling Social Mobilisation – An interdisciplinary exploration of Twitter as a mediating tool for social acts and information networks

    Directory of Open Access Journals (Sweden)

    James D Amor

    2013-10-01

    Full Text Available In recent years, researchers, social commentators and the mass media have turned their attention to shifts in the use of social media for political and social action. This article provides an overview of the recent discussions focusing on how Twitter specifically functions as a mediating tool for social acts. We present findings from a recent pilot project exploring the mechanics of disseminating information via Twitter across a dynamic human network in order to contribute to an understanding of how people use social media to share information and prompt others into action, and outline some approaches for performing this analysis. Taking the perspective of communities of users operating in hybrid spaces, we make recommendations for further research in this field. Key words: Twitter, hybrid spaces, social networks, social acts, information flow

  8. Network-based modeling and intelligent data mining of social media for improving care.

    Science.gov (United States)

    Akay, Altug; Dragomir, Andrei; Erlandsson, Bjorn-Erik

    2015-01-01

    Intelligently extracting knowledge from social media has recently attracted great interest from the Biomedical and Health Informatics community to simultaneously improve healthcare outcomes and reduce costs using consumer-generated opinion. We propose a two-step analysis framework that focuses on positive and negative sentiment, as well as the side effects of treatment, in users' forum posts, and identifies user communities (modules) and influential users for the purpose of ascertaining user opinion of cancer treatment. We used a self-organizing map to analyze word frequency data derived from users' forum posts. We then introduced a novel network-based approach for modeling users' forum interactions and employed a network partitioning method based on optimizing a stability quality measure. This allowed us to determine consumer opinion and identify influential users within the retrieved modules using information derived from both word-frequency data and network-based properties. Our approach can expand research into intelligently mining social media data for consumer opinion of various treatments to provide rapid, up-to-date information for the pharmaceutical industry, hospitals, and medical staff, on the effectiveness (or ineffectiveness) of future treatments.

  9. Coevolution in the model of social interactions: getting closer to real-world networks

    CERN Document Server

    Raducha, Tomasz

    2016-01-01

    We analyze Axelrod's model of social interactions on coevolving complex networks. We introduce four extensions with different mechanisms of edge rewiring. The models are intended to catch two kinds of interactions - preferential attachment, which can be observed in scientists or actors collaborations, and local rewiring, which can be observed in friendship formation in everyday relations. Numerical simulations show that proposed dynamics can lead to power-law distribution nodes' degree and high value of clustering coefficient, while still retaining the small-world effect in three models. All models are characterized by two phase transitions of a different nature. In case of local rewiring we obtain order-disorder discontinuous phase transition even in the thermodynamic limit, while in case of long-distance switching discontinuity disappears in the thermodynamic limit, leaving one continuous phase transition. In addition, we discover a new and universal characteristic of the second transition point - an abrupt...

  10. DARPA Ensemble-Based Modeling Large Graphs & Applications to Social Networks

    Science.gov (United States)

    2015-07-29

    interactions data (Enron, Facebook , Wikipedia, Mobile phones, etc), and large-scale infrastructure data (US roadways). Figure 1. A pictorial overview of...measurement is the connectivity (edge density) of a high school friendship network, it is reasonable to assume that other high schools of similar size will...applications of network science. In large scale social network data (e.g. Facebook , Twitter, cell-phone network) we have access to a set of parameters

  11. Actor-network procedures: Modeling multi-factor authentication, device pairing, social interactions

    CERN Document Server

    Pavlovic, Dusko

    2011-01-01

    As computation spreads from computers to networks of computers, and migrates into cyberspace, it ceases to be globally programmable, but it remains programmable indirectly: network computations cannot be controlled, but they can be steered by local constraints on network nodes. The tasks of "programming" global behaviors through local constraints belong to the area of security. The "program particles" that assure that a system of local interactions leads towards some desired global goals are called security protocols. As computation spreads beyond cyberspace, into physical and social spaces, new security tasks and problems arise. As networks are extended by physical sensors and controllers, including the humans, and interlaced with social networks, the engineering concepts and techniques of computer security blend with the social processes of security. These new connectors for computational and social software require a new "discipline of programming" of global behaviors through local constraints. Since the n...

  12. Complex Networks approach to modeling online social systems: The emergence of computational social science

    OpenAIRE

    2013-01-01

    La presente tesis está dedicada a la descripción, análisis y modelado cuantitativo de sistemas complejos sociales en forma de redes sociales en internet. Mediante el uso de métodos y conceptos provenientes de ciencia de redes, análisis de redes sociales y minería de datos se descubren diferentes patrones estadísticos de los sistemas estudiados. Uno de los objetivos a largo plazo de esta línea de investigación consiste en hacer posible la predicción del comportamiento de sistemas complejos te...

  13. Interests Diffusion in Social Networks

    CERN Document Server

    D'Agostino, Gregorio; De Nicola, Antonio; Tucci, Salvatore

    2015-01-01

    Understanding cultural phenomena on Social Networks (SNs) and exploiting the implicit knowledge about their members is attracting the interest of different research communities both from the academic and the business side. The community of complexity science is devoting significant efforts to define laws, models, and theories, which, based on acquired knowledge, are able to predict future observations (e.g. success of a product). In the mean time, the semantic web community aims at engineering a new generation of advanced services by defining constructs, models and methods, adding a semantic layer to SNs. In this context, a leapfrog is expected to come from a hybrid approach merging the disciplines above. Along this line, this work focuses on the propagation of individual interests in social networks. The proposed framework consists of the following main components: a method to gather information about the members of the social networks; methods to perform some semantic analysis of the Domain of Interest; a p...

  14. 社会网络模型研究论析%Analysis and Discussion on the Model of Social Network

    Institute of Scientific and Technical Information of China (English)

    刘军

    2004-01-01

    Social network analysis is explicitly interested in the relationships among social actors.Focusing on structural variables, it opens up a field of data analysis and model building which is completely different from conventional social statistical methods. Spanning nearly seventy years of research, statistical network analysis has witnessed three stages of models. Beginning from the late 1930s, the first generation of scholars (Moreno, Katz, Heider, etc. ) studied the distribution of various network statistics. The second stage began from the 1970s and continued to the mid 1980s. It dealt primarily with exponential family of probability distributions for directed graphs (p1 model) under the vital assumption of “dyad independence”. Relaxing this assumption, Frank and Strauss (1986), Strauss and Ikeda ( 1990), Wasserman and Pattison (1996) published their pathbreaking papers based on Markov' s random graphs models (p* model and its generalization: logit p*), which brought social network models to a new stage. It is an extremely flexible and complete model dealing with all sorts of structural.aspects of social networks. This substantial “real” structural research should be employed to examine the relational essence of Chinese society.

  15. Quantum social networks

    CERN Document Server

    Cabello, Adan; Lopez-Tarrida, Antonio J; Portillo, Jose R

    2011-01-01

    We introduce a physical approach to social networks (SNs) in which each actor is characterized by a yes-no test on a physical system. This is used to measure whether the interactions originating a SN obey pre-existing properties, as in a classical social network (CSN). As an example of SNs beyond CSNs, we introduce quantum social networks (QSNs) as those in which actor $i$ is characterized by a test of whether or not the system is in a quantum state $|\\psi_i>$. We show that QSNs outperform CSNs for a certain task and some graphs. We identify the simplest of these graphs and show that graphs in which QSNs outperform CSNs are increasingly frequent as the number of vertices increases. We also discuss more general SNs and identify the simplest graphs in which QSNs cannot be outperformed.

  16. Adolescents' Social Network Site Use, Peer Appearance-Related Feedback, and Body Dissatisfaction: Testing a Mediation Model.

    Science.gov (United States)

    de Vries, Dian A; Peter, Jochen; de Graaf, Hanneke; Nikken, Peter

    2016-01-01

    Previous correlational research indicates that adolescent girls who use social network sites more frequently are more dissatisfied with their bodies. However, we know little about the causal direction of this relationship, the mechanisms underlying this relationship, and whether this relationship also occurs among boys to the same extent. The present two-wave panel study (18 month time lag) among 604 Dutch adolescents (aged 11-18; 50.7% female; 97.7% native Dutch) aimed to fill these gaps in knowledge. Structural equation modeling showed that social network site use predicted increased body dissatisfaction and increased peer influence on body image in the form of receiving peer appearance-related feedback. Peer appearance-related feedback did not predict body dissatisfaction and thus did not mediate the effect of social network site use on body dissatisfaction. Gender did not moderate the findings. Hence, social network sites can play an adverse role in the body image of both adolescent boys and girls.

  17. Social Network Infiltration

    Science.gov (United States)

    Plait, Philip

    2008-05-01

    Social networks are websites (or software that distributes media online) where users can distribute content to either a list of friends on that site or to anyone who surfs onto their page, and where those friends can interact and discuss the content. By linking to friends online, the users’ personal content (pictures, songs, favorite movies, diaries, websites, and so on) is dynamically distributed, and can "become viral", that is, get spread rapidly as more people see it and spread it themselves. Social networks are immensely popular around the planet, especially with younger users. The biggest social networks are Facebook and MySpace; an IYA2009 user already exists on Facebook, and one will be created for MySpace (in fact, several NASA satellites such as GLAST and Swift already have successful MySpace pages). Twitter is another network where data distribution is more limited; it is more like a mini-blog, but is very popular. IYA2009 already has a Twitter page, and will be updated more often with relevant information. In this talk I will review the existing social networks, show people how and why they are useful, and give them the tools they need to contribute meaningfully to IYA's online reach.

  18. 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...

  19. Model for Estimating the Potential of Social Networking Sites Usage in Tourism Industry in Bosnia and Herzegovina

    Directory of Open Access Journals (Sweden)

    Edin Osmanbegović

    2014-02-01

    Full Text Available Social networking has taken contemporary business experiences to a new level that cannot be compared with anything that happened so far. Tourism industry and travel booking activities have significantly benefited from such development. Potential travellers can communicate with tourist agencies and operators through social networking sites as well as with tourists who already have visited desired destination or used services from certain operator. This means that tourists can get information directly from actors in tourist activities in order to make their travel decision. Social networking has become large resources from which tourists can make decisions. In this paper it will be given model for estimating the potential of social networking usage by consumers in Bosnia and Herzegovina. According to the given model, estimated potential of social networking usage by consumers is 43.281.660 €, which represents 12.19% of annual touristic expenditure of B&H citizens. Knowledge about mentioned potential is important data for marketers who plan to exploit social networking channel in their marketing efforts.

  20. NEURO FUZZY LINK BASED CLASSIFIER FOR THE ANALYSIS OF BEHAVIOR MODELS IN SOCIAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Indira Priya Ponnuvel

    2014-01-01

    Full Text Available In this study, a new link based classifier using neuro fuzzy logic has been proposed for analyzing the social behavior based on Weblog dataset. In this system, data are processed using a multistage structure. This system provides a diagnosis using a neuro fuzzy link based classifier that analyses the user’s behavior to specific diagnostic categories based on their cluster category in social networks. It uses random walks method to organize the labels. Since the links present in the social network graph frequently represent relationships among the users with respect to social contacts and behaviours, this work observes the links of the graph in order to identify the relationships represented in the graph between the users of the social network based on some new social network metrics and the past behaviour of the users. This work is useful to provide connection between consolidated features of users based on network data and also using the traditional metrics used in the analysis of social network users. From the experiments conducted in this research work, it is observed that the proposed work provides better classification accuracy due to the application of neuro fuzzy classification method in link analysis.

  1. 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

  2. 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 re

  3. Artificial neural network modelling

    CERN Document Server

    Samarasinghe, Sandhya

    2016-01-01

    This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .

  4. A Cloud Theory-Based Trust Computing Model in Social Networks

    Directory of Open Access Journals (Sweden)

    Fengming Liu

    2016-12-01

    Full Text Available How to develop a trust management model and then to efficiently control and manage nodes is an important issue in the scope of social network security. In this paper, a trust management model based on a cloud model is proposed. The cloud model uses a specific computation operator to achieve the transformation from qualitative concepts to quantitative computation. Additionally, this can also be used to effectively express the fuzziness, randomness and the relationship between them of the subjective trust. The node trust is divided into reputation trust and transaction trust. In addition, evaluation methods are designed, respectively. Firstly, the two-dimension trust cloud evaluation model is designed based on node’s comprehensive and trading experience to determine the reputation trust. The expected value reflects the average trust status of nodes. Then, entropy and hyper-entropy are used to describe the uncertainty of trust. Secondly, the calculation methods of the proposed direct transaction trust and the recommendation transaction trust involve comprehensively computation of the transaction trust of each node. Then, the choosing strategies were designed for node to trade based on trust cloud. Finally, the results of a simulation experiment in P2P network file sharing on an experimental platform directly reflect the objectivity, accuracy and robustness of the proposed model, and could also effectively identify the malicious or unreliable service nodes in the system. In addition, this can be used to promote the service reliability of the nodes with high credibility, by which the stability of the whole network is improved.

  5. A social network model for the development of a 'Theory of Mind'

    Science.gov (United States)

    Harré, Michael S.

    2013-02-01

    A "Theory of Mind" is one of the most important skills we as humans have developed; It enables us to infer the mental states and intentions of others, build stable networks of relationships and it plays a central role in our psychological make-up and development. Findings published earlier this year have also shown that we as a species as well as each of us individually benefit from the enlargement of the underlying neuro-anatomical regions that support our social networks, mediated by our Theory of Mind that stabilises these networks. On the basis of such progress and that of earlier work, this paper draws together several different strands from psychology, behavioural economics and network theory in order to generate a novel theoretical representation of the development of our social-cognition and how subsequent larger social networks enables much of our cultural development but at the increased risk of mental disorders.

  6. Psychosocial characteristics and social networks of suicidal prisoners: towards a model of suicidal behaviour in detention.

    Directory of Open Access Journals (Sweden)

    Adrienne Rivlin

    Full Text Available Prisoners are at increased risk of suicide. Investigation of both individual and environmental risk factors may assist in developing suicide prevention policies for prisoners and other high-risk populations. We conducted a matched case-control interview study with 60 male prisoners who had made near-lethal suicide attempts in prison (cases and 60 male prisoners who had not (controls. We compared levels of depression, hopelessness, self-esteem, impulsivity, aggression, hostility, childhood abuse, life events (including events occurring in prison, social support, and social networks in univariate and multivariate models. A range of psychosocial factors was associated with near-lethal self-harm in prisoners. Compared with controls, cases reported higher levels of depression, hopelessness, impulsivity, and aggression, and lower levels of self-esteem and social support (all p values <0.001. Adverse life events and criminal history factors were also associated with near-lethal self-harm, especially having a prior prison spell and having been bullied in prison, both of which remained significant in multivariate analyses. The findings support a model of suicidal behaviour in prisoners that incorporates imported vulnerability factors, clinical factors, and prison experiences, and underscores their interaction. Strategies to reduce self-harm and suicide in prisoners should include attention to such factors.

  7. Social Networks in Silicon Valley

    Institute of Scientific and Technical Information of China (English)

    Joseph Leu

    2006-01-01

    @@ Social network is a dominant, distinguishing characteristic of Silicon Valley. Because innovation entails coping with a high degree of uncertainty,such innovation is particularly dependent on networks.

  8. Foraging Online Social Networks

    NARCIS (Netherlands)

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

    2014-01-01

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

  9. Foraging Online Social Networks

    NARCIS (Netherlands)

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

    2014-01-01

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

  10. Foraging online social networks

    NARCIS (Netherlands)

    Koot, Gijs; Huis in ’t Veld, Mirjam; Hendricksen, Joost; Kaptein, Rianne; Vries, Arnout; Broek, van den Egon L.; Hengst, den M.; Israël, M.; Zeng, D.; Veenman, C.; Wang, A.

    2014-01-01

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

  11. PSN: Portfolio Social Network

    DEFF Research Database (Denmark)

    Cortes, Jordi Magrina; Nizamani, Sarwat; Memon, Nasrullah

    2014-01-01

    In this paper we present a web-based information system which is a portfolio social network (PSN) that provides solutions to the recruiters and job seekers. The proposed system enables users to create portfolio so that he/she can add his specializations with piece of code if any specifically...

  12. A conceptual model for analysing informal learning in online social networks for health professionals.

    Science.gov (United States)

    Li, Xin; Gray, Kathleen; Chang, Shanton; Elliott, Kristine; Barnett, Stephen

    2014-01-01

    Online social networking (OSN) provides a new way for health professionals to communicate, collaborate and share ideas with each other for informal learning on a massive scale. It has important implications for ongoing efforts to support Continuing Professional Development (CPD) in the health professions. However, the challenge of analysing the data generated in OSNs makes it difficult to understand whether and how they are useful for CPD. This paper presents a conceptual model for using mixed methods to study data from OSNs to examine the efficacy of OSN in supporting informal learning of health professionals. It is expected that using this model with the dataset generated in OSNs for informal learning will produce new and important insights into how well this innovation in CPD is serving professionals and the healthcare system.

  13. Social Learning Network Analysis Model to Identify Learning Patterns Using Ontology Clustering Techniques and Meaningful Learning

    Science.gov (United States)

    Firdausiah Mansur, Andi Besse; Yusof, Norazah

    2013-01-01

    Clustering on Social Learning Network still not explored widely, especially when the network focuses on e-learning system. Any conventional methods are not really suitable for the e-learning data. SNA requires content analysis, which involves human intervention and need to be carried out manually. Some of the previous clustering techniques need…

  14. Evolving Social Networks via Friend Recommendations

    OpenAIRE

    Verma, Amit Kumar; Pal, Manjish

    2015-01-01

    A social network grows over a period of time with the formation of new connections and relations. In recent years we have witnessed a massive growth of online social networks like Facebook, Twitter etc. So it has become a problem of extreme importance to know the destiny of these networks. Thus predicting the evolution of a social network is a question of extreme importance. A good model for evolution of a social network can help in understanding the properties responsible for the changes occ...

  15. A simplistic model for identifying prominent web users in directed multiplex social networks: a case study using Twitter networks

    Science.gov (United States)

    Loucif, Hemza; Boubetra, Abdelhak; Akrouf, Samir

    2016-10-01

    This paper aims to describe a new simplistic model dedicated to gauge the online influence of Twitter users based on a mixture of structural and interactional features. The model is an additive mathematical formulation which involves two main parts. The first part serves to measure the influence of the Twitter user on just his neighbourhood covering his followers. However, the second part evaluates the potential influence of the Twitter user beyond the circle of his followers. Particularly, it measures the likelihood that the tweets of the Twitter user will spread further within the social graph through the retweeting process. The model is tested on a data set involving four kinds of real-world egocentric networks. The empirical results reveal that an active ordinary user is more prominent than a non-active celebrity one. A simple comparison is conducted between the proposed model and two existing simplistic approaches. The results show that our model generates the most realistic influence scores due to its dealing with both explicit (structural and interactional) and implicit features.

  16. 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…

  17. 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…

  18. Influence maximization in social networks under an independent cascade-based model

    Science.gov (United States)

    Wang, Qiyao; Jin, Yuehui; Lin, Zhen; Cheng, Shiduan; Yang, Tan

    2016-02-01

    The rapid growth of online social networks is important for viral marketing. Influence maximization refers to the process of finding influential users who make the most of information or product adoption. An independent cascade-based model for influence maximization, called IMIC-OC, was proposed to calculate positive influence. We assumed that influential users spread positive opinions. At the beginning, users held positive or negative opinions as their initial opinions. When more users became involved in the discussions, users balanced their own opinions and those of their neighbors. The number of users who did not change positive opinions was used to determine positive influence. Corresponding influential users who had maximum positive influence were then obtained. Experiments were conducted on three real networks, namely, Facebook, HEP-PH and Epinions, to calculate maximum positive influence based on the IMIC-OC model and two other baseline methods. The proposed model resulted in larger positive influence, thus indicating better performance compared with the baseline methods.

  19. Defining social inclusion of people with intellectual and developmental disabilities: an ecological model of social networks and community participation.

    Science.gov (United States)

    Simplican, Stacy Clifford; Leader, Geraldine; Kosciulek, John; Leahy, Michael

    2015-03-01

    Social inclusion is an important goal for people with intellectual and developmental disabilities, families, service providers, and policymakers; however, the concept of social inclusion remains unclear, largely due to multiple and conflicting definitions in research and policy. We define social inclusion as the interaction between two major life domains: interpersonal relationships and community participation. We then propose an ecological model of social inclusion that includes individual, interpersonal, organizational, community, and socio-political factors. We identify four areas of research that our ecological model of social inclusion can move forward: (1) organizational implementation of social inclusion; (2) social inclusion of people with intellectual and developmental disabilities living with their families, (3) social inclusion of people along a broader spectrum of disability, and (4) the potential role of self-advocacy organizations in promoting social inclusion.

  20. Information and influence propagation in social networks

    CERN Document Server

    Chen, Wei; Lakshmanan, Laks V S

    2013-01-01

    Research on social networks has exploded over the last decade. To a large extent, this has been fueled by the spectacular growth of social media and online social networking sites, which continue growing at a very fast pace, as well as by the increasing availability of very large social network datasets for purposes of research. A rich body of this research has been devoted to the analysis of the propagation of information, influence, innovations, infections, practices and customs through networks. Can we build models to explain the way these propagations occur? How can we validate our models

  1. Social Networks as Marketing Tools

    National Research Council Canada - National Science Library

    NOZHA ERRAGCHA; RABIAA ROMDHANE

    2014-01-01

    The aims of this paper is to reinforce the literature on the digital social networks and their influences on the marketing Having presented and categorized the digital social, networks, we highlighted...

  2. Exploring social representations of adapting to climate change using topic modeling and Bayesian networks

    Directory of Open Access Journals (Sweden)

    Timothy Lynam

    2016-12-01

    In this paper I describe the methods and results of applying topic modeling to 660 micronarratives collected from Australian academics / researchers, government employees, and members of the public in 2010-2011. The narrative fragments focused on adaptation to climate change (CC and hence provide an example of Australian society making sense of an emerging and conflict ridden phenomena. The results of the topic modeling reflect elements of SRs of adaptation to CC that are consistent with findings in the literature as well as being reasonably robust predictors of classes of action in response to CC. Bayesian Network (BN modeling was used to identify relationships among the topics (SR elements and in particular to identify relationships among topics, sentiment, and action. Finally the resulting model and topic modeling results are used to highlight differences in the salience of SR elements among social groups. The approach of linking topic modeling and BN modeling offers a new and encouraging approach to analysis for ongoing research on SRs.

  3. Analytical Solutions for Rumor Spreading Dynamical Model in a Social Network

    Science.gov (United States)

    Fallahpour, R.; Chakouvari, S.; Askari, H.

    2015-03-01

    In this paper, Laplace Adomian decomposition method is utilized for evaluating of spreading model of rumor. Firstly, a succinct review is constructed on the subject of using analytical methods such as Adomian decomposion method, Variational iteration method and Homotopy Analysis method for epidemic models and biomathematics. In continue a spreading model of rumor with consideration of forgetting mechanism is assumed and subsequently LADM is exerted for solving of it. By means of the aforementioned method, a general solution is achieved for this problem which can be readily employed for assessing of rumor model without exerting any computer program. In addition, obtained consequences for this problem are discussed for different cases and parameters. Furthermore, it is shown the method is so straightforward and fruitful for analyzing equations which have complicated terms same as rumor model. By employing numerical methods, it is revealed LADM is so powerful and accurate for eliciting solutions of this model. Eventually, it is concluded that this method is so appropriate for this problem and it can provide researchers a very powerful vehicle for scrutinizing rumor models in diverse kinds of social networks such as Facebook, YouTube, Flickr, LinkedIn and Tuitor.

  4. Global maize trade and food security: implications from a social network model.

    Science.gov (United States)

    Wu, Felicia; Guclu, Hasan

    2013-12-01

    In this study, we developed a social network model of the global trade of maize: one of the most important food, feed, and industrial crops worldwide, and critical to food security. We used this model to analyze patterns of maize trade among nations, and to determine where vulnerabilities in food security might arise if maize availability was decreased due to factors such as diversion to nonfood uses, climatic factors, or plant diseases. Using data on imports and exports from the U.N. Commodity Trade Statistics Database for each year from 2000 to 2009 inclusive, we summarized statistics on volumes of maize trade between pairs of nations for 217 nations. There is evidence of market segregation among clusters of nations; with three prominent clusters representing Europe, Brazil and Argentina, and the United States. The United States is by far the largest exporter of maize worldwide, whereas Japan and the Republic of Korea are the largest maize importers. In particular, the star-shaped cluster of the network that represents U.S. maize trade to other nations indicates the potential for food security risks because of the lack of trade these other nations conduct with other maize exporters. If a scenario arose in which U.S. maize could not be exported in as large quantities, maize supplies in many nations could be jeopardized. We discuss this in the context of recent maize ethanol production and its attendant impacts on food prices elsewhere worldwide.

  5. Social networks: communication and change

    Directory of Open Access Journals (Sweden)

    Gustavo Cardoso

    2011-01-01

    Full Text Available Virtual social networks have brought about the possibility for open and plural debate, where all those with the necessary literacy skills and means are able to participate in the creation and dissemination of information. By pressing political agents and determining the “agenda” of a lot of the media, users demonstrate that we stand at an ideal platform for creating both real social movements and more or less fleeting events, as manifestos or virtual campaigns. Nonetheless, in order to understand the role of virtual social networks in today’s world, we need to answer some prior questions. Are we facing a new communication model, whereby the product of “disinterested” interactivity creates an aura of confidence in disseminated information, often quite higher that that seen in the “old media”? Will that interactivity be a chance to fight-off citizens’ growing detachment with regard to the “res publica”? Will we find in citizen-made journalism, transmitted through virtual social networks, the consecration of a true fourth power? On the other hand, can we call the distinct collective movements we have seen emerging true “social movements”?The present article aims to examine this and other issues that come to the fore in the intricate social world of cyberspace.

  6. Social networks in supervision

    DEFF Research Database (Denmark)

    Lystbæk, Christian Tang

    and practice have focused on conceptual frameworks and practical techniques of promoting reflection through conversation in general and questioning in particular. However, in recent years, supervision research has started to focus on the social and technological aspects of supervision. This calls...... is constituted by the relationality of the actors, not by the actors themselves. In other words, no one acts in a vacuum but rather always under the influence of a wide range of surrounding and interconnected factors. Actors are actors because they are in a networked relationship. Thus, focusing on social...... and space. That involves mobilised an denrolled actos, both animate and inanimate (e.g. books, computers, etc. Actor-network theory defines a symmetry between animate and inanimate, i.e. subjects and objects, because ”human powers increasingly derive from the complex interconnections if human with material...

  7. Graduate Employability: The Perspective of Social Network Learning

    Science.gov (United States)

    Chen, Yong

    2017-01-01

    This study provides a conceptual framework for understanding how the graduate acquire employability through the social network in the Chinese context, using insights from the social network theory. This paper builds a conceptual model of the relationship among social network, social network learning and the graduate employability, and uses…

  8. The Social Networks of Innovation

    DEFF Research Database (Denmark)

    Björk, Jennie; Bergenholtz, Carsten; Magnusson, Mats

    It is a well-known fact in the innovation management literature that social network structures both constrain and facilitate ideation activities within firm boundaries. Still, recent research shows how the impact of social network structures varies across different contexts, depending e......) the characteristics of individuals involved in the given ideation process and 3) the social network activities of these individuals. The dependent variables are based on the idea level. Our research objective is two-fold: We explore how different kinds of social networks develop around varying idea categories...... and explain how particular social network structures facilitate some ideas to fare more successfully than others....

  9. The Social Networks of Innovation

    DEFF Research Database (Denmark)

    Björk, Jennie; Bergenholtz, Carsten; Magnusson, Mats

    It is a well-known fact in the innovation management literature that social network structures both constrain and facilitate ideation activities within firm boundaries. Still, recent research shows how the impact of social network structures varies across different contexts, depending e......) the characteristics of individuals involved in the given ideation process and 3) the social network activities of these individuals. The dependent variables are based on the idea level. Our research objective is two-fold: We explore how different kinds of social networks develop around varying idea categories...... and explain how particular social network structures facilitate some ideas to fare more successfully than others....

  10. Characterizing Pairwise Social Relationships Quantitatively: Interest-Oriented Mobility Modeling for Human Contacts in Delay Tolerant Networks

    Directory of Open Access Journals (Sweden)

    Jiaxu Chen

    2013-01-01

    Full Text Available Human mobility modeling has increasingly drawn the attention of researchers working on wireless mobile networks such as delay tolerant networks (DTNs in the last few years. So far, a number of human mobility models have been proposed to reproduce people’s social relationships, which strongly affect people’s daily life movement behaviors. However, most of them are based on the granularity of community. This paper presents interest-oriented human contacts (IHC mobility model, which can reproduce social relationships on a pairwise granularity. As well, IHC provides two methods to generate input parameters (interest vectors based on the social interaction matrix of target scenarios. By comparing synthetic data generated by IHC with three different real traces, we validate our model as a good approximation for human mobility. Exhaustive experiments are also conducted to show that IHC can predict well the performance of routing protocols.

  11. 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.

  12. 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

  13. 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.

  14. 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

  15. Fitting Social Network Models Using Varying Truncation Stochastic Approximation MCMC Algorithm

    KAUST Repository

    Jin, Ick Hoon

    2013-10-01

    The exponential random graph model (ERGM) plays a major role in social network analysis. However, parameter estimation for the ERGM is a hard problem due to the intractability of its normalizing constant and the model degeneracy. The existing algorithms, such as Monte Carlo maximum likelihood estimation (MCMLE) and stochastic approximation, often fail for this problem in the presence of model degeneracy. In this article, we introduce the varying truncation stochastic approximation Markov chain Monte Carlo (SAMCMC) algorithm to tackle this problem. The varying truncation mechanism enables the algorithm to choose an appropriate starting point and an appropriate gain factor sequence, and thus to produce a reasonable parameter estimate for the ERGM even in the presence of model degeneracy. The numerical results indicate that the varying truncation SAMCMC algorithm can significantly outperform the MCMLE and stochastic approximation algorithms: for degenerate ERGMs, MCMLE and stochastic approximation often fail to produce any reasonable parameter estimates, while SAMCMC can do; for nondegenerate ERGMs, SAMCMC can work as well as or better than MCMLE and stochastic approximation. The data and source codes used for this article are available online as supplementary materials. © 2013 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.

  16. Sustainability and collapse in a coevolutionary model of local resource stocks and behavioral patterns on a social network

    Science.gov (United States)

    Wiedermann, Marc; Donges, Jonathan F.; Heitzig, Jobst; Kurths, Jürgen

    2014-05-01

    When investigating the causes and consequences of global change, the collective behavior of human beings is considered as having a considerable impact on natural systems. In our work, we propose a conceptual coevolutionary model simulating the dynamics of local renewable resources in interaction with simplistic societal agents exploiting those resources. The society is represented by a social network on which social traits may be transmitted between agents. These traits themselves induce a certain rate of exploitation of the resource, leading either to its depletion or sustainable existence. Traits are exchanged probabilistically according to their instantaneous individual payoff, and hence this process depends on the status of the natural resource. At the same time agents may adaptively restructure their set of acquaintances. Connections with agents having a different trait may be broken while new connections with agents of the same trait are established. We investigate which choices of social parameters, like the frequency of social interaction, rationality and rate of social network adaptation, cause the system to end in a sustainable state and, hence, what can be done to avoid a collapse of the entire system. The importance and influence of the social network structure is analyzed by the variation of link-densities in the underlying network topology and shows significant influence on the expected outcome of the model. For a static network with no adaptation we find a robust phase transition between the two different regimes, sustainable and non-sustainable, which co-exist in parameter space. High connectivity within the social network, e.g., high link-densities, in combination with a fast rate of social learning lead to a likely collapse of the entire co-evolutionary system, whereas slow learning and small network connectivity very likely result in the sustainable existence of the natural resources. Collapse may be avoided by an intelligent rewiring, e

  17. Social networks in borderline personality disorder.

    Science.gov (United States)

    Clifton, Allan; Pilkonis, Paul A; McCarty, Christopher

    2007-08-01

    The interpersonal dysfunction that characterizes borderline personality disorder (BPD) has generally been studied using broad global measures, leading to a lack of precision. We report on a novel methodology using social network analysis (SNA) to quantify interactions with others in the patient's social world. We assessed the social networks of 22 clinical patients, diagnosed with either BPD (N = 11) or no personality disorder (No PD; N = 11). The social networks of patients with BPD contained a greater number of former romantic partners, and a greater number of relationships that had been terminated. Mixed model analyses found that the No PD group reported higher levels of positive relationships (e.g., trust, social support) with more central members of their social networks, whereas the BPD group did not discriminate among members of their networks. Results suggest deficits in social cognition for positive relations, but not for negative relations such as interpersonal conflict.

  18. Essays on Social Network Formation in Heterogeneous Populations: Models, Methods, and Empirical Analyses

    OpenAIRE

    Bojanowski, M.J.

    2012-01-01

    The overarching focus of the essays presented in this book pertains to the characteristics of individual actors (such as the industry or nationality associated with a firm), the extent to which the population of actors is heterogeneous with respect to those characteristics, and the ways in which actor characteristics and population heterogeneity influence the process of social network formation and the choices that actors make in these networks. We investigate theoretical, empirical, and meth...

  19. 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.

  20. Interests diffusion in social networks

    Science.gov (United States)

    D'Agostino, Gregorio; D'Antonio, Fulvio; De Nicola, Antonio; Tucci, Salvatore

    2015-10-01

    We provide a model for diffusion of interests in Social Networks (SNs). We demonstrate that the topology of the SN plays a crucial role in the dynamics of the individual interests. Understanding cultural phenomena on SNs and exploiting the implicit knowledge about their members is attracting the interest of different research communities both from the academic and the business side. The community of complexity science is devoting significant efforts to define laws, models, and theories, which, based on acquired knowledge, are able to predict future observations (e.g. success of a product). In the mean time, the semantic web community aims at engineering a new generation of advanced services by defining constructs, models and methods, adding a semantic layer to SNs. In this context, a leapfrog is expected to come from a hybrid approach merging the disciplines above. Along this line, this work focuses on the propagation of individual interests in social networks. The proposed framework consists of the following main components: a method to gather information about the members of the social networks; methods to perform some semantic analysis of the Domain of Interest; a procedure to infer members' interests; and an interests evolution theory to predict how the interests propagate in the network. As a result, one achieves an analytic tool to measure individual features, such as members' susceptibilities and authorities. Although the approach applies to any type of social network, here it is has been tested against the computer science research community. The DBLP (Digital Bibliography and Library Project) database has been elected as test-case since it provides the most comprehensive list of scientific production in this field.

  1. Collectivism culture, HIV stigma and social network support in Anhui, China: a path analytic model.

    Science.gov (United States)

    Zang, Chunpeng; Guida, Jennifer; Sun, Yehuan; Liu, Hongjie

    2014-08-01

    HIV stigma is rooted in culture and, therefore, it is essential to investigate it within the context of culture. The objective of this study was to examine the interrelationships among individualism-collectivism, HIV stigma, and social network support. A social network study was conducted among 118 people living with HIVAIDS in China, who were infected by commercial plasma donation, a nonstigmatized behavior. The Individualism-Collectivism Interpersonal Assessment Inventory (ICIAI) was used to measure cultural norms and values in the context of three social groups, family members, friends, and neighbors. Path analyses revealed (1) a higher level of family ICIAI was significantly associated with a higher level of HIV self-stigma (β=0.32); (2) a higher level of friend ICIAI was associated with a lower level of self-stigma (β=-035); (3) neighbor ICIAI was associated with public stigma (β=-0.61); (4) self-stigman was associated with social support from neighbors (β=-0.27); and (5) public stigma was associated with social support from neighbors (β=-0.24). This study documents that HIV stigma may mediate the relationship between collectivist culture and social network support, providing an empirical basis for interventions to include aspects of culture into HIV intervention strategies.

  2. Leveraging social networks for toxicovigilance.

    Science.gov (United States)

    Chary, Michael; Genes, Nicholas; McKenzie, Andrew; Manini, Alex F

    2013-06-01

    The landscape of drug abuse is shifting. Traditional means of characterizing these changes, such as national surveys or voluntary reporting by frontline clinicians, can miss changes in usage the emergence of novel drugs. Delays in detecting novel drug usage patterns make it difficult to evaluate public policy aimed at altering drug abuse. Increasingly, newer methods to inform frontline providers to recognize symptoms associated with novel drugs or methods of administration are needed. The growth of social networks may address this need. The objective of this manuscript is to introduce tools for using data from social networks to characterize drug abuse. We outline a structured approach to analyze social media in order to capture emerging trends in drug abuse by applying powerful methods from artificial intelligence, computational linguistics, graph theory, and agent-based modeling. First, we describe how to obtain data from social networks such as Twitter using publicly available automated programmatic interfaces. Then, we discuss how to use artificial intelligence techniques to extract content useful for purposes of toxicovigilance. This filtered content can be employed to generate real-time maps of drug usage across geographical regions. Beyond describing the real-time epidemiology of drug abuse, techniques from computational linguistics can uncover ways that drug discussions differ from other online conversations. Next, graph theory can elucidate the structure of networks discussing drug abuse, helping us learn what online interactions promote drug abuse and whether these interactions differ among drugs. Finally, agent-based modeling relates online interactions to psychological archetypes, providing a link between epidemiology and behavior. An analysis of social media discussions about drug abuse patterns with computational linguistics, graph theory, and agent-based modeling permits the real-time monitoring and characterization of trends of drugs of abuse. These

  3. 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...

  4. Modeling individual and collective opinion in online social networks: drivers of choice behavior and effects of marketing interventions

    NARCIS (Netherlands)

    Koster, S.E.; Langley, D.J.

    2013-01-01

    We investigate factors influencing choice behavior in online social networks. We use twitter data from a Dutch television talent show. In study one, we implement a nested conditional logit model with latent classes. We find heterogeneous effects. For two latent classes, cognitive factors most strong

  5. A Logic for Diffusion in Social Networks

    NARCIS (Netherlands)

    Christoff, Z.; Hansen, J.U.

    2015-01-01

    This paper introduces a general logical framework for reasoning about diffusion processes within social networks. The new "Logic for Diffusion in Social Networks" is a dynamic extension of standard hybrid logic, allowing to model complex phenomena involving several properties of agents. We provide a

  6. Intercultural Communication in Online Social Networking Discourse

    Science.gov (United States)

    Chen, Hsin-I

    2017-01-01

    This article presents a case study that examines how an online social networking community is constituted through intercultural discourse on the part of one learner sojourning in the US. Using Byram's model of intercultural communicative competence, this study examines the learner's naturalistic communication in a social networking site (SNS). The…

  7. Predicting the evolution of social networks with life cycle events

    OpenAIRE

    Sharmeen, F Fariya; Arentze, TA Theo; Timmermans, HJP Harry

    2015-01-01

    This paper presents a model of social network evolution, to predict and simulate changes in social networks induced by lifecycle events. We argue that social networks change with lifecycle events, and we extend a model of friendship selection to incorporate these dynamics of personal social networks. The model uses theories of homophily and reciprocity and is formulated in a random utility maximization framework to predict the formation of social ties between individuals in the population. It...

  8. Applications of Social Network Analysis

    Science.gov (United States)

    Thilagam, P. Santhi

    A social network [2] is a description of the social structure between actors, mostly persons, groups or organizations. It indicates the ways in which they are connected with each other by some relationship such as friendship, kinship, finance exchange etc. In a nutshell, when the person uses already known/unknown people to create new contacts, it forms social networking. The social network is not a new concept rather it can be formed when similar people interact with each other directly or indirectly to perform particular task. Examples of social networks include a friendship networks, collaboration networks, co-authorship networks, and co-employees networks which depict the direct interaction among the people. There are also other forms of social networks, such as entertainment networks, business Networks, citation networks, and hyperlink networks, in which interaction among the people is indirect. Generally, social networks operate on many levels, from families up to the level of nations and assists in improving interactive knowledge sharing, interoperability and collaboration.

  9. Collaboration in Social Networks

    CERN Document Server

    Dall'Asta, Luca; Pin, Paolo

    2011-01-01

    The very notion of social network implies that linked individuals interact repeatedly with each other. This allows them not only to learn successful strategies and adapt to them, but also to condition their own behavior on the behavior of others, in a strategic forward looking manner. Game theory of repeated games shows that these circumstances are conducive to the emergence of collaboration in simple games of two players. We investigate the extension of this concept to the case where players are engaged in a local contribution game and show that rationality and credibility of threats identify a class of Nash equilibria -- that we call "collaborative equilibria" -- that have a precise interpretation in terms of sub-graphs of the social network. For large network games, the number of such equilibria is exponentially large in the number of players. When incentives to defect are small, equilibria are supported by local structures whereas when incentives exceed a threshold they acquire a non-local nature, which r...

  10. 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

  11. Social Network Analysis Based on Network Motifs

    OpenAIRE

    2014-01-01

    Based on the community structure characteristics, theory, and methods of frequent subgraph mining, network motifs findings are firstly introduced into social network analysis; the tendentiousness evaluation function and the importance evaluation function are proposed for effectiveness assessment. Compared with the traditional way based on nodes centrality degree, the new approach can be used to analyze the properties of social network more fully and judge the roles of the nodes effectively. I...

  12. 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…

  13. 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…

  14. Testing knowledge sharing effectiveness: trust, motivation, leadership style, workplace spirituality and social network embedded model

    Directory of Open Access Journals (Sweden)

    Rahman Muhammad Sabbir

    2015-12-01

    Full Text Available The aim of this inquiry is to investigate the relationships among the antecedents of knowledge sharing effectiveness under the position of non-academic staff of higher learning institutions through an empirical test of a conceptual model consisting of trust, extrinsic and intrinsic motivation, leadership style, workplace spirituality and online social network. This study used the respondents from the non-academic staff of higher learning institutions in Malaysia (n = 200, utilizing a self-administered survey questionnaire. The structural equation modeling approach was used to test the proposed hypotheses. The outcomes indicate that all the antecedents play a substantial function in knowledge sharing effectiveness. In addition, perceived risk plays a mediating role between trust and knowledge sharing effectiveness. On the other hand, this research also proved the communication skill also plays a mediating role between leadership style and knowledge sharing effectiveness. This study contributes to pioneering empirical findings on knowledge sharing literature under the scope of the non-academic staff perspective.

  15. Elgg 18 Social Networking

    CERN Document Server

    Costello, Cash

    2012-01-01

    This book provides more than just a step-by-step guide to installing and using Elgg. It includes practical advice gained through experience on what it takes to deploy and maintain an Elgg-based site. If you are a software developer or are familiar with PHP, it provides both a tutorial-based introduction and a quick reference guide so that you can quickly extend and customize Elgg. If you want to create a social networking site using Elgg and do not have a background in software development, this book provides all the information and advice that you need written just for you. If you are a devel

  16. Dynamics of deceptive interactions in social networks

    CERN Document Server

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

    2015-01-01

    In this paper we examine the role of lies in human social relations by implementing some salient characteristics of deceptive interactions into an opinion formation model, so as to describe the dynamical behaviour of a social network more realistically. In this model we take into account such basic properties of social networks as the dynamics of the intensity of interactions, the influence of public opinion, and the fact that in every human interaction it might be convenient to deceive or withhold information depending on the instantaneous situation of each individual in the network. We find that lies shape the topology of social networks, especially the formation of tightly linked, small communities with loose connections between them. We also find that agents with a larger proportion of deceptive interactions are the ones that connect communities of different opinion, and in this sense they have substantial centrality in the network. We then discuss the consequences of these results for the social behaviou...

  17. Digital Social Network Mining for Topic Discovery

    Science.gov (United States)

    Moradianzadeh, Pooya; Mohi, Maryam; Sadighi Moshkenani, Mohsen

    Networked computers are expanding more and more around the world, and digital social networks becoming of great importance for many people's work and leisure. This paper mainly focused on discovering the topic of exchanging information in digital social network. In brief, our method is to use a hierarchical dictionary of related topics and words that mapped to a graph. Then, with comparing the extracted keywords from the context of social network with graph nodes, probability of relation between context and desired topics will be computed. This model can be used in many applications such as advertising, viral marketing and high-risk group detection.

  18. Multistage Campaigning in Social Networks

    CERN Document Server

    Farajtabar, Mehrdad; Harati, Sahar; Song, Le; Zha, Hongyuan

    2016-01-01

    We consider the problem of how to optimize multi-stage campaigning over social networks. The dynamic programming framework is employed to balance the high present reward and large penalty on low future outcome in the presence of extensive uncertainties. In particular, we establish theoretical foundations of optimal campaigning over social networks where the user activities are modeled as a multivariate Hawkes process, and we derive a time dependent linear relation between the intensity of exogenous events and several commonly used objective functions of campaigning. We further develop a convex dynamic programming framework for determining the optimal intervention policy that prescribes the required level of external drive at each stage for the desired campaigning result. Experiments on both synthetic data and the real-world MemeTracker dataset show that our algorithm can steer the user activities for optimal campaigning much more accurately than baselines.

  19. On sampling social networking services

    OpenAIRE

    Wang, Baiyang

    2012-01-01

    This article aims at summarizing the existing methods for sampling social networking services and proposing a faster confidence interval for related sampling methods. It also includes comparisons of common network sampling techniques.

  20. Social Interaction in Learning Networks

    NARCIS (Netherlands)

    Sloep, Peter

    2009-01-01

    The original publication is available from www.springerlink.com. Sloep, P. (2009). Social Interaction in Learning Networks. In R. Koper (Ed.), Learning Network Services for Professional Development (pp 13-15). Berlin, Germany: Springer Verlag.

  1. Social Networks in Silicon Valley

    Institute of Scientific and Technical Information of China (English)

    Joseph; Leu

    2006-01-01

      Social network is a dominant, distinguishing characteristic of Silicon Valley. Because innovation entails coping with a high degree of uncertainty,such innovation is particularly dependent on networks.……

  2. An actor-based model of social network influence on adolescent body size, screen time, and playing sports.

    Directory of Open Access Journals (Sweden)

    David A Shoham

    Full Text Available Recent studies suggest that obesity may be "contagious" between individuals in social networks. Social contagion (influence, however, may not be identifiable using traditional statistical approaches because they cannot distinguish contagion from homophily (the propensity for individuals to select friends who are similar to themselves or from shared environmental influences. In this paper, we apply the stochastic actor-based model (SABM framework developed by Snijders and colleagues to data on adolescent body mass index (BMI, screen time, and playing active sports. Our primary hypothesis was that social influences on adolescent body size and related behaviors are independent of friend selection. Employing the SABM, we simultaneously modeled network dynamics (friendship selection based on homophily and structural characteristics of the network and social influence. We focused on the 2 largest schools in the National Longitudinal Study of Adolescent Health (Add Health and held the school environment constant by examining the 2 school networks separately (N = 624 and 1151. Results show support in both schools for homophily on BMI, but also for social influence on BMI. There was no evidence of homophily on screen time in either school, while only one of the schools showed homophily on playing active sports. There was, however, evidence of social influence on screen time in one of the schools, and playing active sports in both schools. These results suggest that both homophily and social influence are important in understanding patterns of adolescent obesity. Intervention efforts should take into consideration peers' influence on one another, rather than treating "high risk" adolescents in isolation.

  3. Sustainable use of renewable resources in a stylized social-ecological network model under heterogeneous resource distribution

    Science.gov (United States)

    Barfuss, Wolfram; Donges, Jonathan F.; Wiedermann, Marc; Lucht, Wolfgang

    2017-04-01

    Human societies depend on the resources ecosystems provide. Particularly since the last century, human activities have transformed the relationship between nature and society at a global scale. We study this coevolutionary relationship by utilizing a stylized model of private resource use and social learning on an adaptive network. The latter process is based on two social key dynamics beyond economic paradigms: boundedly rational imitation of resource use strategies and homophily in the formation of social network ties. The private and logistically growing resources are harvested with either a sustainable (small) or non-sustainable (large) effort. We show that these social processes can have a profound influence on the environmental state, such as determining whether the private renewable resources collapse from overuse or not. Additionally, we demonstrate that heterogeneously distributed regional resource capacities shift the critical social parameters where this resource extraction system collapses. We make these points to argue that, in more advanced coevolutionary models of the planetary social-ecological system, such socio-cultural phenomena as well as regional resource heterogeneities should receive attention in addition to the processes represented in established Earth system and integrated assessment models.

  4. 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.

  5. The effect of networked social interactions on the attainability of the safe operating space in a stylized social-ecological model

    Science.gov (United States)

    Barfuss, Wolfram; Donges, Jonathan; Wiedermann, Marc; Lucht, Wolfgang

    2016-04-01

    Humanity depends on the resources ecosystems provide. Especially in the last century, human activities have changed the relationship between nature and society at a global scale. Here, we study this interdependent relationship with a generic model of the coevolution of individual resource use and social preference formation. The latter is an adaptive network process based on two social key interactions beyond economic paradigms: imitation and homophily. The individual resources follow a logistically growing stock harvested with either a sustainable (small) or non-sustainable (large) effort. We are able to show that these kinds of social processes can have a profound influence on environmental state, such as determining whether the regional renewable resources collapse from overuse or not. We demonstrate additionally that heterogeneously distributed resource capacities among the nodes of the network shift the critical social parameters where this resource extraction system collapses. We make these points to argue that, in more elaborate and sophisticated implementations, such social phenomena as well as heterogeneities should receive attention in social-ecological systems models as well as Earth system and integrated assessment models. It is a necessary first step to better understand the underlying dynamics and interactions of planetary boundaries and the safe and just operating space for humanity.

  6. Connections Matter: Social Networks and Lifespan Health in Primate Translational Models

    Science.gov (United States)

    McCowan, Brenda; Beisner, Brianne; Bliss-Moreau, Eliza; Vandeleest, Jessica; Jin, Jian; Hannibal, Darcy; Hsieh, Fushing

    2016-01-01

    Humans live in societies full of rich and complex relationships that influence health. The ability to improve human health requires a detailed understanding of the complex interplay of biological systems that contribute to disease processes, including the mechanisms underlying the influence of social contexts on these biological systems. A longitudinal computational systems science approach provides methods uniquely suited to elucidate the mechanisms by which social systems influence health and well-being by investigating how they modulate the interplay among biological systems across the lifespan. In the present report, we argue that nonhuman primate social systems are sufficiently complex to serve as model systems allowing for the development and refinement of both analytical and theoretical frameworks linking social life to health. Ultimately, developing systems science frameworks in nonhuman primate models will speed discovery of the mechanisms that subserve the relationship between social life and human health. PMID:27148103

  7. Churn in Social Networks

    Science.gov (United States)

    Karnstedt, Marcel; Hennessy, Tara; Chan, Jeffrey; Basuchowdhuri, Partha; Hayes, Conor; Strufe, Thorsten

    In the past, churn has been identified as an issue across most industry sectors. In its most general sense it refers to the rate of loss of customers from a company's customer base. There is a simple reason for the attention churn attracts: churning customers mean a loss of revenue. Emerging from business spaces like telecommunications (telcom) and broadcast providers, where churn is a major issue, it is also regarded as a crucial problem in many other businesses, such as online games creators, but also online social networks and discussion sites. Companies aim at identifying the risk of churn in its early stages, as it is usually much cheaper to retain a customer than to try to win him or her back. If this risk can be accurately predicted, marketing departments can target customers efficiently with tailored incentives to prevent them from leaving.

  8. Digital Stylometry: Linking Profiles Across Social Networks

    OpenAIRE

    Vosoughi, Soroush; Zhou, Helen; Roy, Deb

    2015-01-01

    There is an ever growing number of users with accounts on multiple social media and networking sites. Consequently, there is increasing interest in matching user accounts and profiles across different social networks in order to create aggregate profiles of users. In this paper, we present models for Digital Stylometry, which is a method for matching users through stylometry inspired techniques. We experimented with linguistic, temporal, and combined temporal-linguistic models for matching us...

  9. 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…

  10. 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…

  11. 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...

  12. Risk aversion and social networks

    NARCIS (Netherlands)

    Kovářík, J.; van der Leij, M.J.

    2014-01-01

    This paper first investigates empirically the relationship between risk aversion and social network structure in a large group of undergraduate students. We find that risk aversion is strongly correlated to local network clustering, that is, the probability that one has a social tie to friends of

  13. A novel opinion dynamics model based on expanded observation ranges and individuals’ social influences in social networks

    Science.gov (United States)

    Diao, Su-Meng; Liu, Yun; Zeng, Qing-An; Luo, Gui-Xun; Xiong, Fei

    2014-12-01

    In this paper, we propose an opinion dynamics model in order to investigate opinion evolution and interactions and the behavior of individuals. By introducing social influence and its feedback mechanism, the proposed model can highlight the heterogeneity of individuals and reproduce realistic online opinion interactions. It can also expand the observation range of affected individuals. Combining psychological studies on the social impact of majorities and minorities, affected individuals update their opinions by balancing social impact from both supporters and opponents. It can be seen that complete consensus is not always obtained. When the initial density of either side is greater than 0.8, the enormous imbalance leads to complete consensus. Otherwise, opinion clusters consisting of a set of tightly connected individuals who hold similar opinions appear. Moreover, a tradeoff is discovered between high interaction intensity and low stability with regard to observation ranges. The intensity of each interaction is negatively correlated with observation range, while the stability of each individual’s opinion positively affects the correlation. Furthermore, the proposed model presents the power-law properties in the distribution of individuals’ social influences, which is in agreement with people’s daily cognition. Additionally, it is proven that the initial distribution of individuals’ social influences has little effect on the evolution.

  14. 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...... sources. These results point out the roles non-market arrangements, such as social networks, can play in mitigating market inefficiencies in poor rural markets....... 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...

  15. Signed Networks in Social Media

    CERN Document Server

    Leskovec, Jure; 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 classical theory of structural balance tends to capture certain common patterns of interaction, but that it is also at odds with some of the fundamental phenomena we observe --- particularly related to the evolving, directed nature of these on-line networks. We then develop an alternate theory of status that better explains the observed edge signs and provides insights into the underlying social mechanisms. Our work provides one of the first large-scale evaluations of theories of signed networks using on-line datasets, as ...

  16. Preserving Communities in Anonymized Social Networks

    Directory of Open Access Journals (Sweden)

    Alina Campan

    2015-04-01

    Full Text Available Social media and social networks are embedded in our society to a point that could not have been imagined only ten years ago. Facebook, LinkedIn, and Twitter are already well known social networks that have a large audience in all age groups. The amount of data that those social sites gather from their users is continually increasing and this data is very valuable for marketing, research, and various other purposes. At the same time, this data usually contain a significant amount of sensitive information which should be protected against unauthorized disclosure. To protect the privacy of individuals, this data must be anonymized such that the risk of re-identification of specific individuals is very low. In this paper we study if anonymized social networks preserve existing communities from the original social networks. To perform this study, we introduce two approaches to measure the community preservation between the initial network and its anonymized version. In the first approach we simply count how many nodes from the original communities remained in the same community after the processes of anonymization and de-anonymization. In the second approach we consider the community preservation for each node individually. Specifically, for each node, we compare the original and final communities to which the node belongs. To anonymize social networks we use two models, namely, k-anonymity for social networks and k-degree anonymity. To determine communities in social networks we use an existing community detection algorithm based on modularity quality function. Our experiments on publically available datasets show that anonymized social networks satisfactorily preserve the community structure of their original networks.

  17. The Power of Social Networks: A Model for Weaving the Scholarship of Teaching and Learning into Institutional Culture

    Directory of Open Access Journals (Sweden)

    Andrea L. Williams

    2013-09-01

    micro, the meso, and the macro. The authors argue that for SoTL to take root in organizational cultures, there must be 1 effective communication and dissemination of SoTL activity across all levels, 2 well established social networks and links between these levels (nodes, and 3 sustained support by senior administrationThe authors conclude by suggesting ways their model could be tested.

  18. Growing model of online social network.%在线社会网络演化模型

    Institute of Scientific and Technical Information of China (English)

    李稳国; 崔宪普; 邓曙光; 肖卫初

    2011-01-01

    Based on ideas of previous network models,an online social network evolution model is presented by analyzing topology, characteristics and evolution of online social networks. A dynamic weight is introduced into the online social evolution model.Theoretical analysis and simulation show that the online network evolution model is scale-free and small world with power-law degrees, node degrees and strength degrees, and with large clustering coefficient and small path length, which is adjustable. The scale-free and small world properties correspond with real-life online society network.%在分析在线社会网络的拓扑结构、特征及演化规律的基础上,借鉴了前人网络模型的思想,提出了在线社会网络演化模型,引入动态的加权方式,提出了一种在线社会网络演化模型.理论分析和仿真表明:在线社会网络演化模型具有无标度和小世界特性,点权,边权、度分布呈现幂律特性,具有较多的簇系数、较小的路径长度且可调.这种无标度和小世界特性与现实中的在线社会网络较为一致.

  19. Assessing Argumentative Representation with Bayesian Network Models in Debatable Social Issues

    Science.gov (United States)

    Zhang, Zhidong; Lu, Jingyan

    2014-01-01

    This study seeks to obtain argumentation models, which represent argumentative processes and an assessment structure in secondary school debatable issues in the social sciences. The argumentation model was developed based on mixed methods, a combination of both theory-driven and data-driven methods. The coding system provided a combing point by…

  20. 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,…

  1. Social networks a framework of computational intelligence

    CERN Document Server

    Chen, Shyi-Ming

    2014-01-01

    This volume provides the audience with an updated, in-depth and highly coherent material on the conceptually appealing and practically sound information technology of Computational Intelligence applied to the analysis, synthesis and evaluation of social networks. The volume involves studies devoted to key issues of social networks including community structure detection in networks, online social networks, knowledge growth and evaluation, and diversity of collaboration mechanisms.  The book engages a wealth of methods of Computational Intelligence along with well-known techniques of linear programming, Formal Concept Analysis, machine learning, and agent modeling.  Human-centricity is of paramount relevance and this facet manifests in many ways including personalized semantics, trust metric, and personal knowledge management; just to highlight a few of these aspects. The contributors to this volume report on various essential applications including cyber attacks detection, building enterprise social network...

  2. Temporal fidelity in dynamic social networks

    DEFF Research Database (Denmark)

    Stopczynski, Arkadiusz; Sapiezynski, Piotr; Pentland, Alex ‘Sandy’

    2015-01-01

    of the network dynamics can be used to inform the process of measuring social networks. The details of measurement are of particular importance when considering dynamic processes where minute-to-minute details are important, because collection of physical proximity interactions with high temporal resolution......It has recently become possible to record detailed social interactions in large social systems with high resolution. As we study these datasets, human social interactions display patterns that emerge at multiple time scales, from minutes to months. On a fundamental level, understanding...... is difficult and expensive. Here, we consider the dynamic network of proximity-interactions between approximately 500 individuals participating in the Copenhagen Networks Study. We show that in order to accurately model spreading processes in the network, the dynamic processes that occur on the order...

  3. SOCIAL NETWORKS AND INTERPERSONAL COMMUNICATION

    OpenAIRE

    Veronica GHEORGHIȚĂ; Alexandrina PĂDUREȚU

    2014-01-01

    Social networks visible influence people's ability to interact and communicate. Extending social circles by establishing virtual links involves a number of positive aspects such as: instant access to options for interaction, sharing of information to large communities of people, intensification of acts of communication, high levels of feedback and trust with people with whom we communicate. On the other hand, social networks adversely affects communication by decreasing the interaction face t...

  4. 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...... induces different career choices for individuals from different social groups. This further translates into stable occupational segregation equilibria in the labor market. We derive the conditions for wage and unemployment inequality in the segregation equilibria and characterize first and second best...

  5. Cluster-size entropy in the Axelrod model of social influence: small-world networks and mass media.

    Science.gov (United States)

    Gandica, Y; Charmell, A; Villegas-Febres, J; Bonalde, I

    2011-10-01

    We study the Axelrod's cultural adaptation model using the concept of cluster-size entropy S(c), which gives information on the variability of the cultural cluster size present in the system. Using networks of different topologies, from regular to random, we find that the critical point of the well-known nonequilibrium monocultural-multicultural (order-disorder) transition of the Axelrod model is given by the maximum of the S(c)(q) distributions. The width of the cluster entropy distributions can be used to qualitatively determine whether the transition is first or second order. By scaling the cluster entropy distributions we were able to obtain a relationship between the critical cultural trait q(c) and the number F of cultural features in two-dimensional regular networks. We also analyze the effect of the mass media (external field) on social systems within the Axelrod model in a square network. We find a partially ordered phase whose largest cultural cluster is not aligned with the external field, in contrast with a recent suggestion that this type of phase cannot be formed in regular networks. We draw a q-B phase diagram for the Axelrod model in regular networks.

  6. 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.

  7. Social Business Models

    Directory of Open Access Journals (Sweden)

    Maria Cristina Enache

    2015-09-01

    Full Text Available A Social Business embraces networks of people to create business value. A Social Business connects people to expertise. It enable individuals – whether customers, partners or employees – to form networks to generate new sources of innovation, foster creativity, and establish greater reach and exposure to new business opportunities. It establishes a foundational level of trust across these business networks and, thus, a willingness to openly share information. It empowers these networks with the collaborative, gaming and analytical tools needed for members to engage each other and creatively solve business challenges. A Social business strives to remove unnecessary boundaries between experts inside the company and experts in the marketplace. It embraces the tools and leadership models that support capturing knowledge and insight from many sources, allowing it to quickly sense changes in customer mood, employee sentiment or process efficiencies. It utilizes analytics and social connections inside and outside the company to solve business problems and capture new business opportunities. A Social Business leverages these social networks to speed up business, gaining real time insight to make quicker and better decisions. It gets information to customers and partners in new ways -- faster. Supported by ubiquitous access on mobile devices and new ways of connecting and working together in the Cloud and on open platforms, a Social Business turns time and location from constraints into advantages. Business is free to occur when and where it delivers the greatest value, allowing the organization to adapt quickly to the changing marketplace. We believe the most effective approach to enabling a Social Business centers around helping people discover expertise, develop social networks and capitalize on relationships.

  8. SOCIAL NETWORKS AND INTERPERSONAL COMMUNICATION

    Directory of Open Access Journals (Sweden)

    Veronica GHEORGHIȚĂ

    2014-11-01

    Full Text Available Social networks visible influence people's ability to interact and communicate. Extending social circles by establishing virtual links involves a number of positive aspects such as: instant access to options for interaction, sharing of information to large communities of people, intensification of acts of communication, high levels of feedback and trust with people with whom we communicate. On the other hand, social networks adversely affects communication by decreasing the interaction face to face, by imposing superficial communications experiences, grammatical and spelling erosion of the language. Therefore, the study aims to capture the spread of social networks, their use and impact on interpersonal communication. More specifically, they look for the answer to the question: what is the nature of interpersonal communication that is found on social networking sites: personal, emotional, private or shared, informal, and public?

  9. 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.

  10. Anti-Social Networking

    Directory of Open Access Journals (Sweden)

    Chris Allen

    2014-01-01

    Full Text Available With research highlighting the growing incidence of public opposition to the building of mosques and the innovative use of social networking, especially Facebook, to disseminate and garner support for such opposition, a pilot study sought to investigate this in relation to the proposed Dudley “super mosque.” Focusing on the Facebook group Stop Dudley Super Mosque and Islamic Village, members were engaged online to explore why they opposed the mosque. Some of the emergent themes included planning and location, inclusion and public investment as well as those relating to notions of identity, heritage, otherness, and Islamification. Overt racist and Islamophobic reasons were also identified. The sense of political disconnect of members is also considered. Concluding with a contextualization of the findings within the existing body of scholarly output, in particular the building of mosques and Islamophobia, having recognized how spaces such as Facebook have potential to function as sites for research and method also, an extended methodological consideration is also included.

  11. Introduction to Social Network Analysis

    Science.gov (United States)

    Zaphiris, Panayiotis; Ang, Chee Siang

    Social Network analysis focuses on patterns of relations between and among people, organizations, states, etc. It aims to describe networks of relations as fully as possible, identify prominent patterns in such networks, trace the flow of information through them, and discover what effects these relations and networks have on people and organizations. Social network analysis offers a very promising potential for analyzing human-human interactions in online communities (discussion boards, newsgroups, virtual organizations). This Tutorial provides an overview of this analytic technique and demonstrates how it can be used in Human Computer Interaction (HCI) research and practice, focusing especially on Computer Mediated Communication (CMC). This topic acquires particular importance these days, with the increasing popularity of social networking websites (e.g., youtube, myspace, MMORPGs etc.) and the research interest in studying them.

  12. 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...

  13. Managing relationships and communications in higher education efficiently through digital social networks: The importance of the relational coordination model

    National Research Council Canada - National Science Library

    Alexander Lacayo Mendoza; Carmen de Pablos Heredero

    2016-01-01

      Digital social networks have proven to be of great support for organizations that are increasingly using new forms of social communication every day, seeking to improve their productivity and competitiveness...

  14. 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.

  15. Semantic mining of social networks

    CERN Document Server

    Tang, Jie

    2015-01-01

    The first kinds of questions we try to answer are: What are the fundamental factors that form the different categories of social ties? How have reciprocal relationships been developed fro parasocial relationships? How do connected users further form groups? Another theme addressed in this book is the study of social influence. Social influence occurs when one's opinions, emotions, or behaviors are affected by others, intentionally or unintentionally. Considerable research has been conducted to verify the existence of social influence in various networks.

  16. The model of microblog message diffusion based on complex social network

    Science.gov (United States)

    Zhang, Wei; Bai, Shu-Ying; Jin, Rui

    2014-05-01

    Microblog is a micromessage communication network in which users are the nodes and the followship between users are the edges. Sina Weibo is a typical case of these microblog service websites. As the enormous scale of nodes and complex links in the network, we choose a sample network crawled in Sina Weibo as the base of empirical analysis. The study starts with the analysis of its topological features, and brings in epidemiological SEIR model to explore the mode of message spreading throughout the microblog network. It is found that the network is obvious small-world and scale-free, which made it succeed in transferring messages and failed in resisting negative influence. In addition, the paper focuses on the rich nodes as they constitute a typical feature of Sina Weibo. It is also found that whether the message starts with a rich node will not account for its final coverage. Actually, the rich nodes always play the role of pivotal intermediaries who speed up the spreading and make the message known by much more people.

  17. Networked Social Enterprises: A New Model of Community Schooling for Disadvantaged Neighborhoods Facing Challenging Times

    Directory of Open Access Journals (Sweden)

    Kirstin Kerr

    2016-06-01

    Full Text Available Community schools have long been accepted as an institutional mechanism for intervening in the relationship between poverty, poor educational outcomes, and limited life chances. At a time when public services are being retracted, and disadvantaged places are being increasingly left to struggle, community schools are poised to become more important in offering a response to the needs of children, families, and communities in these places. Yet, despite their apparent promise, community schools remain badly under-conceptualized. As an international field, research on community schooling has rarely articulated or questioned how—by providing additional learning and leisure opportunities and personal and social supports—community schools might create a viable intervention in the relationship between poverty and poor outcomes. This paper explicitly addresses this significant challenge. Conceptualizing empirical findings emerging from a research-practice partnership, it identifies the core features of a new institutional design for community schools which can help to clarify their potential contribution to addressing disadvantage. Marking a considerable shift from a traditional design of simply adding new services to the school day, it argues that community schools will need to operate as social enterprises with networked governance arrangements, and to develop strategies which engage with children’s social ecologies, and are risk-reducing and resilience-building within these. This, in turn, sets a new agenda for significantly advancing the field of community schooling by further defining—conceptually and empirically—the core elements of a new institutional design as identified here.

  18. Fundamental structures of dynamic social networks.

    Science.gov (United States)

    Sekara, Vedran; Stopczynski, Arkadiusz; Lehmann, Sune

    2016-09-06

    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 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 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 unnecessary. Starting from 5-min time slices, we uncover dynamic social structures expressed on multiple timescales. On the hourly timescale, we find that gatherings are fluid, with members coming and going, but organized via a stable core of individuals. Each core represents a social context. Cores exhibit a pattern of recurring meetings across weeks and months, each with varying degrees of regularity. Taken together, these findings provide a powerful simplification of the social network, where cores represent fundamental structures expressed with strong temporal and spatial regularity. Using this framework, we explore the complex interplay between social and geospatial behavior, documenting how the formation of cores is preceded by coordination behavior in the communication networks and demonstrating that social behavior can be predicted with high precision.

  19. The Social Network of Tracer Variations and O(100) Uncertain Photochemical Parameters in the Community Atmosphere Model

    Science.gov (United States)

    Lucas, D. D.; Labute, M.; Chowdhary, K.; Debusschere, B.; Cameron-Smith, P. J.

    2014-12-01

    Simulating the atmospheric cycles of ozone, methane, and other radiatively important trace gases in global climate models is computationally demanding and requires the use of 100's of photochemical parameters with uncertain values. Quantitative analysis of the effects of these uncertainties on tracer distributions, radiative forcing, and other model responses is hindered by the "curse of dimensionality." We describe efforts to overcome this curse using ensemble simulations and advanced statistical methods. Uncertainties from 95 photochemical parameters in the trop-MOZART scheme were sampled using a Monte Carlo method and propagated through 10,000 simulations of the single column version of the Community Atmosphere Model (CAM). The variance of the ensemble was represented as a network with nodes and edges, and the topology and connections in the network were analyzed using lasso regression, Bayesian compressive sensing, and centrality measures from the field of social network theory. Despite the limited sample size for this high dimensional problem, our methods determined the key sources of variation and co-variation in the ensemble and identified important clusters in the network topology. Our results can be used to better understand the flow of photochemical uncertainty in simulations using CAM and other climate models. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and supported by the DOE Office of Science through the Scientific Discovery Through Advanced Computing (SciDAC).

  20. Subjective well-being associated with size of social network and social support of elderly.

    Science.gov (United States)

    Wang, Xingmin

    2016-06-01

    The current study examined the impact of size of social network on subjective well-being of elderly, mainly focused on confirmation of the mediator role of perceived social support. The results revealed that both size of social network and perceived social support were significantly correlated with subjective well-being. Structural equation modeling indicated that perceived social support partially mediated size of social network to subjective well-being. The final model also revealed significant both paths from size of social network to subjective well-being through perceived social support. The findings extended prior researches and provided valuable evidence on how to promote mental health of the elderly.

  1. Hypothesis testing in animal social networks.

    Science.gov (United States)

    Croft, Darren P; Madden, Joah R; Franks, Daniel W; James, Richard

    2011-10-01

    Behavioural ecologists are increasingly using social network analysis to describe the social organisation of animal populations and to test hypotheses. However, the statistical analysis of network data presents a number of challenges. In particular the non-independent nature of the data violates the assumptions of many common statistical approaches. In our opinion there is currently confusion and uncertainty amongst behavioural ecologists concerning the potential pitfalls when hypotheses testing using social network data. Here we review what we consider to be key considerations associated with the analysis of animal social networks and provide a practical guide to the use of null models based on randomisation to control for structure and non-independence in the data.

  2. Long division unites - long union divides, a model for social network evolution

    CERN Document Server

    Jian, Jiang; Michel, Pezeril; Qiuping-Alexandre, Wang

    2013-01-01

    A remarkable phenomenon in the time evolution of many networks such as cultural, political, national and economic systems, is the recurrent transition between the states of union and division of nodes. In this work, we propose a phenomenological modeling, inspired by the maxim "long union divides and long division unites", in order to investigate the evolutionary characters of these networks composed of the entities whose behaviors are dominated by these two events. The nodes are endowed with quantities such as identity, ingredient, richness (power), openness (connections), age, distance, interaction etc. which determine collectively the evolution in a probabilistic way. Depending on a tunable parameter, the time evolution of this model is mainly an alternative domination of union or division state, with a possible state of final union dominated by one single node.

  3. 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.

  4. Cooperation on Social Networks and Its Robustness

    CERN Document Server

    Antonioni, Alberto

    2012-01-01

    In this work we have used computer models of social-like networks to show by extensive numerical simulations that cooperation in evolutionary games can emerge and be stable on this class of networks. The amounts of cooperation reached are at least as much as in scale-free networks but here the population model is more realistic. Cooperation is robust with respect to different strategy update rules, population dynamics, and payoff computation. Only when straight average payoff is used or there is high strategy or network noise does cooperation decrease in all games and disappear in the Prisoner's Dilemma.

  5. Organizational networks and social capital

    DEFF Research Database (Denmark)

    Svendsen, Gunnar Lind Haase; Waldstrøm, Christian

    2013-01-01

    This chapter presents a framework for understanding organizational networks and social capital through the lens of “social capital ownership” as well as the private and collective goods provided through this ownership. More specifically, it argues that ownership of social capital in organizations...... is closely connected to four types of social capital – two belonging to the bridging social capital type, and two belonging to the bonding social capital type. The chapter first reviews literature on organizational social capital and then directly focuses on ownership of social capital in organizations......, as well as the derived benefits, or losses. Next, the chapter presents an empirical case apt to illustrate the theoretical findings in part one, namely the nineteenth-century Danish Cooperative Dairy Movement (Svendsen and Svendsen 2004). It is demonstrated how social capital among Danish peasants...

  6. Organizational networks and social capital

    DEFF Research Database (Denmark)

    Svendsen, Gunnar Lind Haase; Waldstrøm, Christian

    2013-01-01

    This chapter presents a framework for understanding organizational networks and social capital through the lens of “social capital ownership” as well as the private and collective goods provided through this ownership. More specifically, it argues that ownership of social capital in organizations...... is closely connected to four types of social capital – two belonging to the bridging social capital type, and two belonging to the bonding social capital type. The chapter first reviews literature on organizational social capital and then directly focuses on ownership of social capital in organizations......, as well as the derived benefits, or losses. Next, the chapter presents an empirical case apt to illustrate the theoretical findings in part one, namely the nineteenth-century Danish Cooperative Dairy Movement (Svendsen and Svendsen 2004). It is demonstrated how social capital among Danish peasants...

  7. On Social and Economic Networks

    NARCIS (Netherlands)

    A. Galeotti

    2005-01-01

    textabstractYou can call it a clan, or a network, or a family, or a group of friends. The way you call it is not relevant. What matters is that it exists and often you will need one. A large body of empirical work shows that networks are pervasive in social and economic interactions. This book conta

  8. Social networks and research output

    NARCIS (Netherlands)

    Ductor, L.; Fafchamps, M.; Goyal, S.; van der Leij, M.J.

    2014-01-01

    We study how knowledge about the social network of an individual researcher - as embodied in his coauthor relations - helps us in developing a more accurate prediction of his future productivity. We find that incorporating information about coauthor networks leads to a modest improvement in the accu

  9. Autotagging Facebook: Social Network Context Improves Photo Annotation

    OpenAIRE

    Zickler, Todd; Stone, Zak; Darrell, Trevor

    2008-01-01

    Most personal photos that are shared online are embedded in some form of social network, and these social networks are a potent source of contextual information that can be leveraged for automatic image understanding. In this paper, we investigate the utility of social network context for the task of automatic face recognition in personal photographs. We combine face recognition scores with social context in a conditional random field (CRF) model and apply this model to label faces in photos ...

  10. Why Care About Social Networks in Travel Demand Forecasting? Testing the Predictive Power of Social Attributes in Modeling Discretionary Trip Frequencies

    NARCIS (Netherlands)

    Sharmeen, F.; Sivakumar, A.

    2017-01-01

    In recent years, social networks are gaining increasingly more attention in explaining personal travel behavior. A fundamental question in this regard is what value does social network data add to explain and predict travel patterns? Although several studies have documented the empirical

  11. Kinship, family and social network

    Directory of Open Access Journals (Sweden)

    2000-12-01

    Full Text Available There is considerable overlap between Le Play's mid-eighteenth-century household model map and the regional TFR map of central-southern Europe in the 1980s. The author examines the overall structure of relationships involved in Le Play's typology and observes that both the stem-family and the unstable family area in the Southern Europe are marked by a small, close-knit network of strong ties, with kinship predominance. Vice versa, the social support hinges upon a network of kin in the stem-family area, upon an alliance among different kindred units in the unstable Mediterranean area. All this leads to formulating a hypothesis of a tri-partite model for Western European relationship models. How can we explain the relationship between family predominance as anthropological embedding and family collapse as demographic reaction? The author reconsiders this question in the light of Festinger's cognitive dissonance theory and Elder's 'principle of accentuation': different, regionally rooted, family and kinship patterns "react" in contact with an appropriate reagent, such as the macro-process of modernisation, generating different patterns of today's demographic behaviour.

  12. 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…

  13. Prisoner's dilemma on real social networks: revisited.

    Science.gov (United States)

    Cameron, Sharon M; Cintron-Arias, Ariel

    2013-01-01

    Prisoner's Dilemma is a game theory model used to describe altruistic behavior seen in various populations. This theoretical game is important in understanding why a seemingly selfish strategy does persist and spread throughout a population that is mixing homogeneously at random. For a population with structure determined by social interactions, Prisoner's Dilemma brings to light certain requirements for the altruistic strategy to become established. Monte Carlo simulations of Prisoner's Dilemma are carried out using both simulated social networks and a dataset of a real social network. In both scenarios we confirm the requirements for the persistence of altruism in a population.

  14. 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.

  15. Binary Classification Method of Social Network Users

    Directory of Open Access Journals (Sweden)

    I. A. Poryadin

    2017-01-01

    Full Text Available The subject of research is a binary classification method of social network users based on the data analysis they have placed. Relevance of the task to gain information about a person by examining the content of his/her pages in social networks is exemplified. The most common approach to its solution is a visual browsing. The order of the regional authority in our country illustrates that its using in school education is needed. The article shows restrictions on the visual browsing of pupil’s pages in social networks as a tool for the teacher and the school psychologist and justifies that a process of social network users’ data analysis should be automated. Explores publications, which describe such data acquisition, processing, and analysis methods and considers their advantages and disadvantages. The article also gives arguments to support a proposal to study the classification method of social network users. One such method is credit scoring, which is used in banks and credit institutions to assess the solvency of clients. Based on the high efficiency of the method there is a proposal for significant expansion of its using in other areas of society. The possibility to use logistic regression as the mathematical apparatus of the proposed method of binary classification has been justified. Such an approach enables taking into account the different types of data extracted from social networks. Among them: the personal user data, information about hobbies, friends, graphic and text information, behaviour characteristics. The article describes a number of existing methods of data transformation that can be applied to solve the problem. An experiment of binary gender-based classification of social network users is described. A logistic model obtained for this example includes multiple logical variables obtained by transforming the user surnames. This experiment confirms the feasibility of the proposed method. Further work is to define a system

  16. Communication competence, social support, and depression among college students: a model of facebook and face-to-face support network influence.

    Science.gov (United States)

    Wright, Kevin B; Rosenberg, Jenny; Egbert, Nicole; Ploeger, Nicole A; Bernard, Daniel R; King, Shawn

    2013-01-01

    This study examined the influence of the social networking site Facebook and face-to-face support networks on depression among (N = 361) college students. The authors used the Relational Health Communication Competence Model as a framework for examining the influence of communication competence on social support network satisfaction and depression. Moreover, they examined the influence of interpersonal and social integrative motives as exogenous variables. On the basis of previous work, the authors propose and test a theoretical model using structural equation modeling. The results indicated empirical support for the model, with interpersonal motives predicting increased face-to-face and computer-mediated competence, increased social support satisfaction with face-to-face and Facebook support, and lower depression scores. The implications of the findings for theory, key limitations, and directions for future research are discussed.

  17. Privacy Analysis in Mobile Social Networks

    DEFF Research Database (Denmark)

    Sapuppo, Antonio

    2012-01-01

    Nowadays, mobile social networks are capable of promoting social networking benefits during physical meetings, in order to leverage interpersonal affinities not only among acquaintances, but also between strangers. Due to their foundation on automated sharing of personal data in the physical...... factors: inquirer, purpose of disclosure, access & control of the disclosed information, location familiarity and current activity of the user. This research can serve as relevant input for the design of privacy management models in mobile social networks....... surroundings of the user, these networks are subject to crucial privacy threats. Privacy management systems must be capable of accurate selection of data disclosure according to human data sensitivity evaluation. Therefore, it is crucial to research and comprehend an individual's personal information...

  18. ONLINE SOCIAL NETWORK INTERNETWORKING ANALYSIS

    Directory of Open Access Journals (Sweden)

    Bassant E.Youssef

    2014-10-01

    Full Text Available Online social networks (OSNs contain data about users, their relations, interests and daily activities andthe great value of this data results in ever growing popularity of OSNs. There are two types of OSNs data,semantic and topological. Both can be used to support decision making processes in many applicationssuch as in information diffusion, viral marketing and epidemiology. Online Social network analysis (OSNAresearch is used to maximize the benefits gained from OSNs’ data. This paper provides a comprehensive study of OSNs and OSNA to provide analysts with the knowledge needed to analyse OSNs. OSNs’internetworking was found to increase the wealth of the analysed data by depending on more than one OSNas the source of the analysed data. Paper proposes a generic model of OSNs’ internetworking system that an analyst can rely on. Twodifferent data sources in OSNs were identified in our efforts to provide a thorough study of OSNs, whichare the OSN User data and the OSN platform data. Additionally, we propose a classification of the OSNUser data according to its analysis models for different data types to shed some light into the current usedOSNA methodologies. We also highlight the different metrics and parameters that analysts can use toevaluate semantic or topologic OSN user data. Further, we present a classification of the other data typesand OSN platform data that can be used to compare the capabilities of different OSNs whether separate orin a OSNs’ internetworking system. To increase analysts’ awareness about the available tools they can use,we overview some of the currently publically available OSNs’ datasets and simulation tools and identifywhether they are capable of being used in semantic, topological OSNA, or both. The overview identifiesthat only few datasets includes both data types (semantic and topological and there are few analysis toolsthat can perform analysis on both data types. Finally paper present a scenario that

  19. MODELLING SOCIAL CAPITAL AND GROWTH

    OpenAIRE

    Chou, Yuan K.

    2002-01-01

    This paper proposes three theoretical growth models incorporating social capital, based on varied expositions on the concept of social capital and the empirical evidence gathered to date. In these models, social capital impacts growth by assisting in the accumulation of human capital, by affecting financial development through its effects on collective trust and social norms, and by facilitating networking between firms that result in the creation and diffusion of business and technological i...

  20. Cluster size entropy in the Axelrod model of social influence: small-world networks and mass media

    CERN Document Server

    Gandica, Yérali; Villegas-Febres, J; Bonalde, I

    2011-01-01

    We study the Axelrod's cultural adaptation model using the concept of cluster size entropy, $S_{c}$ that gives information on the variability of the cultural cluster size present in the system. Using networks of different topologies, from regular to random, we find that the critical point of the well-known nonequilibrium monocultural-multicultural (order-disorder) transition of the Axelrod model is unambiguously given by the maximum of the $S_{c}(q)$ distributions. The width of the cluster entropy distributions can be used to qualitatively determine whether the transition is first- or second-order. By scaling the cluster entropy distributions we were able to obtain a relationship between the critical cultural trait $q_c$ and the number $F$ of cultural features in regular networks. We also analyze the effect of the mass media (external field) on social systems within the Axelrod model in a square network. We find a new partially ordered phase whose largest cultural cluster is not aligned with the external fiel...

  1. Social networks and environmental outcomes.

    Science.gov (United States)

    Barnes, Michele L; Lynham, John; Kalberg, Kolter; Leung, PingSun

    2016-06-07

    Social networks can profoundly affect human behavior, which is the primary force driving environmental change. However, empirical evidence linking microlevel social interactions to large-scale environmental outcomes has remained scarce. Here, we leverage comprehensive data on information-sharing networks among large-scale commercial tuna fishers to examine how social networks relate to shark bycatch, a global environmental issue. We demonstrate that the tendency for fishers to primarily share information within their ethnic group creates segregated networks that are strongly correlated with shark bycatch. However, some fishers share information across ethnic lines, and examinations of their bycatch rates show that network contacts are more strongly related to fishing behaviors than ethnicity. Our findings indicate that social networks are tied to actions that can directly impact marine ecosystems, and that biases toward within-group ties may impede the diffusion of sustainable behaviors. Importantly, our analysis suggests that enhanced communication channels across segregated fisher groups could have prevented the incidental catch of over 46,000 sharks between 2008 and 2012 in a single commercial fishery.

  2. A framework for online social networking features

    Directory of Open Access Journals (Sweden)

    Mohsen Shafiei Nikabadi

    2014-06-01

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

  3. 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.

  4. Coevolutionary modeling in network formation

    KAUST Repository

    Al-Shyoukh, Ibrahim

    2014-12-03

    Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.

  5. Knowledge in a Social Network

    OpenAIRE

    Angere, Staffan

    2010-01-01

    The purpose of this paper is to present a formal model of social net- works suitable for studying questions in social epistemology. We show how to use this model, in conjunction with a computer program for simulating groups of inquirers, to draw conclusions about the epistemological prop- erties of different social practices. This furnishes us with the beginnings of a systematic research program in social epistemology, from which to approach problems pertaining to epistemic value, optimal org...

  6. Knowledge in a Social Network

    OpenAIRE

    Angere, Staffan

    2010-01-01

    The purpose of this paper is to present a formal model of social net- works suitable for studying questions in social epistemology. We show how to use this model, in conjunction with a computer program for simulating groups of inquirers, to draw conclusions about the epistemological prop- erties of different social practices. This furnishes us with the beginnings of a systematic research program in social epistemology, from which to approach problems pertaining to epistemic value, optimal org...

  7. Extreme Thouless effect in a minimal model of dynamic social networks

    Science.gov (United States)

    Bassler, K. E.; Liu, Wenjia; Schmittmann, B.; Zia, R. K. P.

    2015-04-01

    In common descriptions of phase transitions, first-order transitions are characterized by discontinuous jumps in the order parameter and normal fluctuations, while second-order transitions are associated with no jumps and anomalous fluctuations. Outside this paradigm are systems exhibiting "mixed-order" transitions displaying a mixture of these characteristics. When the jump is maximal and the fluctuations range over the entire range of allowed values, the behavior has been coined an "extreme Thouless effect." Here we report findings of such a phenomenon in the context of dynamic, social networks. Defined by minimal rules of evolution, it describes a population of extreme introverts and extroverts, who prefer to have contacts with, respectively, no one or everyone. From the dynamics, we derive an exact distribution of microstates in the stationary state. With only two control parameters, NI ,E (the number of each subgroup), we study collective variables of interest, e.g., X , the total number of I -E links, and the degree distributions. Using simulations and mean-field theory, we provide evidence that this system displays an extreme Thouless effect. Specifically, the fraction X /(NINE) jumps from 0 to 1 (in the thermodynamic limit) when NI crosses NE, while all values appear with equal probability at NI=NE .

  8. Extreme Thouless effect in a minimal model of dynamic social networks.

    Science.gov (United States)

    Bassler, K E; Liu, Wenjia; Schmittmann, B; Zia, R K P

    2015-04-01

    In common descriptions of phase transitions, first-order transitions are characterized by discontinuous jumps in the order parameter and normal fluctuations, while second-order transitions are associated with no jumps and anomalous fluctuations. Outside this paradigm are systems exhibiting "mixed-order" transitions displaying a mixture of these characteristics. When the jump is maximal and the fluctuations range over the entire range of allowed values, the behavior has been coined an "extreme Thouless effect." Here we report findings of such a phenomenon in the context of dynamic, social networks. Defined by minimal rules of evolution, it describes a population of extreme introverts and extroverts, who prefer to have contacts with, respectively, no one or everyone. From the dynamics, we derive an exact distribution of microstates in the stationary state. With only two control parameters, N(I,E) (the number of each subgroup), we study collective variables of interest, e.g., X, the total number of I-E links, and the degree distributions. Using simulations and mean-field theory, we provide evidence that this system displays an extreme Thouless effect. Specifically, the fraction X/(N(I)N(E)) jumps from 0 to 1 (in the thermodynamic limit) when N(I) crosses N(E), while all values appear with equal probability at N(I)=N(E).

  9. Cooperative and Competitive Dynamics Model for Information Propagation in Online Social Networks

    Directory of Open Access Journals (Sweden)

    Yaming Zhang

    2014-01-01

    Full Text Available Traditional empirical models of propagation consider individual contagion as an independent process, thus spreading in isolation manner. In this paper, we study how different contagions interact with each other as they spread through the network in order to propose an alternative dynamics model for information propagation. The proposed model is a novel combination of Lotka-Volterra cooperative model and competitive model. It is assumed that the interaction of one message on another is flexible instead of always negative. We prove that the impact of competition depends on the critical speed of the messages. By analyzing the differential equations, one or two stable equilibrium points can be found under certain conditions. Simulation results not only show the correctness of our theoretical analyses but also provide a more attractive conclusion. Different types of messages could coexist in the condition of high critical speed and intense competitive environment, or vice versa. The messages will benefit from the high critical speed when they are both competitive, and adopting a Tit-for-Tat strategy is necessary during the process of information propagation.

  10. 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.

  11. Evolution model of online social networks based on complex networks%复杂网络中的在线社交网络演化模型

    Institute of Scientific and Technical Information of China (English)

    王景丽; 许立波; 庞超逸

    2015-01-01

    在线社交网络是一种广泛存在的社会网络,其节点度遵循幂率分布规律,但对于其结构演化模型方面的相关研究还不多. 基于复杂网络理论研究在线社交网络内部结构特征,提出一种结合内增长、外增长及内部边更替的演化模型,借助平均场理论分析该模型的拓扑特性,实验和理论分析表明由该模型生成的网络,其度分布服从幂率分布,且通过调整参数,幂率指数在1~3,能较好地反映不同类型的真实在线社交网络的度分布特征,因此具有广泛适用性.%As a widespread social network , the node degree of online social networks has been proven by many re-searchers to follow the power-law distribution .However , there are few studies modeling the evolution of its struc-ture.In this paper , we propose an evolution model that combines the inside growth , outside growth , and edge re-placement based on those of complex networks .The topology properties of this model are analyzed using the mean-field theory .Experiment and theoretical analyses show that the degree of a node in a network generated by the new evolution model follows the power-law distribution and that the power-law index ranges between 1 and 3.Therefore , the proposed model can better reflect the node degree distribution characteristics of different types of real online so -cial networks and will have wide applicability .

  12. Burstiness and aging in social temporal networks

    CERN Document Server

    Moinet, Antoine; Pastor-Satorras, Romualdo

    2014-01-01

    The presence of burstiness in temporal social networks, revealed by a power law form of the waiting time distribution of consecutive interactions, is expected to produce aging effects in the corresponding time-integrated network. Here we propose an analytically tractable model, in which interactions among the agents are ruled by a renewal process, and that is able to reproduce this aging behavior. We develop an analytic solution for the topological properties of the integrated network produced by the model, finding that the time translation invariance of the degree distribution is broken. We validate our predictions against numerical simulations, and we check for the presence of aging effects in a empirical temporal network, ruled by bursty social interactions.

  13. Social media: opportunities for quality improvement and lessons for providers-a networked model for patient-centered care through digital engagement.

    Science.gov (United States)

    Bornkessel, Alexandra; Furberg, Robert; Lefebvre, R Craig

    2014-07-01

    Social media brings a new dimension to health care for patients, providers, and their support networks. Increasing evidence demonstrates that patients who are more actively involved in their healthcare experience have better health outcomes and incur lower costs. In the field of cardiology, social media are proposed as innovative tools for the education and update of clinicians, physicians, nurses, and medical students. This article reviews the use of social media by healthcare providers and patients and proposes a model of "networked care" that integrates the use of digital social networks and platforms by both patients and providers and offers recommendations for providers to optimize their use and understanding of social media for quality improvement.

  14. Social Networks and Welfare in Future Animal Management

    Directory of Open Access Journals (Sweden)

    Paul Koene

    2014-03-01

    Full Text Available 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.

  15. 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.

  16. BRAND COMMUNICATION ON SOCIAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Otilia-Elena PLATON

    2015-07-01

    Full Text Available The communication represents a basic element for the marketing activity that helps companies to achieve their objectives. Building long-term relationships between brands and consumers is one of the most important objectives pursued by marketers. This involves brand communication and creating multiple connections with consumers, even in the online environment. From this point of view, social networks proved to be an effective way of linking brands and consumers online. This paper aims to present some aspects involved by the usage of social networks in brand communication by analyzing several examples of online marketing campaigns implemented on Facebook on the occasion of Valentine's Day by six different brands.

  17. Social Networks as Marketing Tools

    Directory of Open Access Journals (Sweden)

    NOZHA ERRAGCHA

    2014-05-01

    Full Text Available The aims of this paper is to reinforce the literature on the digital social networks and their influences on the marketing Having presented and categorized the digital social, networks, we highlighted, the opportunities which brings Web2.0 to the marketing. The advent of Web2.0 imposed fundamental changes Which required the revalorization of the role of the consumer in the marketing approach. Indeed, this one is not passive any more, but it becomes a co-value-creating for the company

  18. Semantic network mapping of religious material: testing multi-agent computer models of social theories against real-world data.

    Science.gov (United States)

    Lane, Justin E

    2015-11-01

    Agent-based modeling allows researchers to investigate theories of complex social phenomena and subsequently use the model to generate new hypotheses that can then be compared to real-world data. However, computer modeling has been underutilized in regard to the understanding of religious systems, which often require very complex theories with multiple interacting variables (Braxton et al. in Method Theory Study Relig 24(3):267-290, 2012. doi: 10.1163/157006812X635709 ; Lane in J Cogn Sci Relig 1(2):161-180, 2013). This paper presents an example of how computer modeling can be used to explore, test, and further understand religious systems, specifically looking at one prominent theory of religious ritual. The process is continuous: theory building, hypothesis generation, testing against real-world data, and improving the model. In this example, the output of an agent-based model of religious behavior is compared against real-world religious sermons and texts using semantic network analysis. It finds that most religious materials exhibit unique scale-free small-world properties and that a concept's centrality in a religious schema best predicts its frequency of presentation. These results reveal that there adjustments need to be made to existing models of religious ritual systems and provide parameters for future models. The paper ends with a discussion of implications for a new multi-agent model of doctrinal ritual behaviors as well as propositions for further interdisciplinary research concerning the multi-agent modeling of religious ritual behaviors.

  19. Dynamics in online social networks

    CERN Document Server

    Grabowicz, Przemyslaw A; Eguiluz, Victor M

    2012-01-01

    An increasing number of today's social interactions occurs using online social media as communication channels. Some online social networks have become extremely popular in the last decade. They differ among themselves in the character of the service they provide to online users. For instance, Facebook can be seen mainly as a platform for keeping in touch with close friends and relatives, Twitter is used to propagate and receive news, LinkedIn facilitates the maintenance of professional contacts, Flickr gathers amateurs and professionals of photography, etc. Albeit different, all these online platforms share an ingredient that pervades all their applications. There exists an underlying social network that allows their users to keep in touch with each other and helps to engage them in common activities or interactions leading to a better fulfillment of the service's purposes. This is the reason why these platforms share a good number of functionalities, e.g., personal communication channels, broadcasted status...

  20. Navigating Social Networks

    Science.gov (United States)

    Hamblin, DeAnna; Bartlett, Marilyn J.

    2013-01-01

    The authors note that when it comes to balancing free speech and schools' responsibilities, the online world is largely uncharted waters. Questions remain about the rights of both students and teachers in the world of social media. Although the lower courts have ruled that students' freedom of speech rights offer them some protection for…

  1. Navigating Social Networks

    Science.gov (United States)

    Hamblin, DeAnna; Bartlett, Marilyn J.

    2013-01-01

    The authors note that when it comes to balancing free speech and schools' responsibilities, the online world is largely uncharted waters. Questions remain about the rights of both students and teachers in the world of social media. Although the lower courts have ruled that students' freedom of speech rights offer them some protection for…

  2. Group Recommendation in Social Networks

    Science.gov (United States)

    2011-01-01

    the Facebook social graph are connected to each other via relationships. Bret Taylor is a fan of the Coca - Cola page, and Bret Taylor and Arjun...even used for business promotions like organizing events and taking surveys etc. Consider for example, if you would like to conduct a survey it...takes a lot of effort in terms of the promotion to reach out to the intended audience. Using social networks targeting the audience and reaching out

  3. Social networks user: current research

    Directory of Open Access Journals (Sweden)

    Agadullina E.R.

    2015-12-01

    Full Text Available The purpose of this article is to review current research studies focusing on the users of Facebook and their behaviors in social networks. This review is organized into two sections: 1 social-demographic characteristics (Age, Gender, Nationality; 2 personality characteristics (Neuroticism, Extraversion, Openness-to-Experience, Agreeableness, Conscientiousness, Narcissism, Self-esteem. The results showed that the information in the personal profile and online behavior are strongly connected with socio-demographic and personality characteristics

  4. The interaction evolution model of mass incidents with delay in a social network

    Science.gov (United States)

    Huo, Liang'an; Ma, Chenyang

    2017-10-01

    Recent years have witnessed rapid development of information technology. Today, modern media is widely used for the purpose of spreading information rapidly and widely. In particular, through micro-blog promotions, individuals tend to express their viewpoints and spread information on the internet, which could easily lead to public opinions. Moreover, government authorities also disseminate official information to guide public opinion and eliminate any incorrect conjecture. In this paper, a dynamical model with two delays is investigated to exhibit the interaction evolution between the public and official opinion fields in network mass incidents. Based on the theory of differential equations, the interaction mechanism between two public opinion fields in a micro-blog environment is analyzed. Two delays are proposed in the model to depict the response delays of public and official opinion fields. Some stable conditions are obtained, which shows that Hopf bifurcation can occur as delays cross critical values. Further, some numerical simulations are carried out to verify theoretical results. Our model indicates that there exists a golden time for government intervention, which should be emphasized given the impact of modern media and inaccurate rumors. If the government releases official information during the golden time, mass incidents on the internet can be controlled effectively.

  5. SOCIAL NETWORK EFFECTS ON ROMANTIC RELATIONSHIP

    Directory of Open Access Journals (Sweden)

    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.

  6. Social networks and factor markets

    DEFF Research Database (Denmark)

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

    2017-01-01

    We investigate the role of an indigenous social network in Ethiopia, the iddir, in facilitating factor market transactions among smallholder farmers. We use a detailed longitudinal household survey data and employ a fixed effects estimation to identify the effect of iddir membership on factor...... market transactions among farmers. We find that joining an iddir network improves households’ access to land, labour and credit transactions. Our findings also hint that iddir networks may crowd-out borrowing from local moneylenders (locally referred as ‘Arata Abedari’), a relatively expensive credit...

  7. Data Mining on Social Interaction Networks

    OpenAIRE

    Atzmueller, Martin

    2013-01-01

    Social media and social networks have already woven themselves into the very fabric of everyday life. This results in a dramatic increase of social data capturing various relations between the users and their associated artifacts, both in online networks and the real world using ubiquitous devices. In this work, we consider social interaction networks from a data mining perspective - also with a special focus on real-world face-to-face contact networks: We combine data mining and social netwo...

  8. Social Scholarship: Applying Social Networking Technologies to Research Practices

    Science.gov (United States)

    Greenhow, Christine

    2009-01-01

    Participatory web-based technologies have the potential to change the way scholars engage in scholarship. One reason Web 2.0 technologies, such as online social networking, are not widely integrated in PreK-12 and postsecondary education is the lack of modeling by educators. Their lack of research-based best practices limits the ability to…

  9. Undermining and Strengthening Social Networks through Network Modification

    Science.gov (United States)

    Mellon, Jonathan; Yoder, Jordan; Evans, Daniel

    2016-10-01

    Social networks have well documented effects at the individual and aggregate level. Consequently it is often useful to understand how an attempt to influence a network will change its structure and consequently achieve other goals. We develop a framework for network modification that allows for arbitrary objective functions, types of modification (e.g. edge weight addition, edge weight removal, node removal, and covariate value change), and recovery mechanisms (i.e. how a network responds to interventions). The framework outlined in this paper helps both to situate the existing work on network interventions but also opens up many new possibilities for intervening in networks. In particular use two case studies to highlight the potential impact of empirically calibrating the objective function and network recovery mechanisms as well as showing how interventions beyond node removal can be optimised. First, we simulate an optimal removal of nodes from the Noordin terrorist network in order to reduce the expected number of attacks (based on empirically predicting the terrorist collaboration network from multiple types of network ties). Second, we simulate optimally strengthening ties within entrepreneurial ecosystems in six developing countries. In both cases we estimate ERGM models to simulate how a network will endogenously evolve after intervention.

  10. The use of social networking services and their relationship with the big five personality model and job satisfaction in Korea.

    Science.gov (United States)

    Kim, Hyondong; Chung, Yang Woon

    2014-10-01

    Social networking services (SNSs) have been garnering attention from society due to their recent rapid growth. This study examines whether SNS use can affect the relationship between the Big Five personality model and individual job satisfaction. Based on a sample of 1,452 workers in Korea, the results of this study indicate that the Big Five personality model (extroversion, agreeableness, and neuroticism) was significantly related to individual job satisfaction. Further, SNS use moderated the relationship between extroversion and neuroticism with individual job satisfaction. Also, SNS use was found to increase job satisfaction of Korean workers who are more extroverted, while it also affected job satisfaction of Korean workers with low agreeableness. As SNS use plays an important role in the workplace, it is necessary to realize and appreciate the importance of SNSs in shaping and promoting job satisfaction of working individuals.

  11. Discovering Typed Communities in Mobile Social Networks

    Institute of Scientific and Technical Information of China (English)

    Huai-Yu Wan; You-Fang Lin; Zhi-Hao Wu; Hou-Kuan Huang

    2012-01-01

    Mobile social networks,which consist of mobile users who communicate with each other using cell phones,are reflections of people's interactions in social lives.Discovering typed communities (e.g.,family communities or corporate communities) in mobile social networks is a very promising problem.For example,it can help mobile operators to determine the target users for precision marketing.In this paper we propose discovering typed communities in mobile social networks by utilizing the labels of relationships between users.We use the user logs stored by mobile operators,including communication and user movement records,to collectively label all the relationships in a network,by employing an undirected probabilistic graphical model,i.e.,conditional random fields.Then we use two methods to discover typed communities based on the results of relationship labeling:one is simply retaining or cutting relationships according to their labels,and the other is using sophisticated weighted community detection algorithms.The experimental results show that our proposed framework performs well in terms of the accuracy of typed community detection in mobile social networks.

  12. Social contagions on interdependent lattice networks.

    Science.gov (United States)

    Shu, Panpan; Gao, Lei; Zhao, Pengcheng; Wang, Wei; Stanley, H Eugene

    2017-03-16

    Although an increasing amount of research is being done on the dynamical processes on interdependent spatial networks, knowledge of how interdependent spatial networks influence the dynamics of social contagion in them is sparse. Here we present a novel non-Markovian social contagion model on interdependent spatial networks composed of two identical two-dimensional lattices. We compare the dynamics of social contagion on networks with different fractions of dependency links and find that the density of final recovered nodes increases as the number of dependency links is increased. We use a finite-size analysis method to identify the type of phase transition in the giant connected components (GCC) of the final adopted nodes and find that as we increase the fraction of dependency links, the phase transition switches from second-order to first-order. In strong interdependent spatial networks with abundant dependency links, increasing the fraction of initial adopted nodes can induce the switch from a first-order to second-order phase transition associated with social contagion dynamics. In networks with a small number of dependency links, the phase transition remains second-order. In addition, both the second-order and first-order phase transition points can be decreased by increasing the fraction of dependency links or the number of initially-adopted nodes.

  13. Social Networks and Political Parties in Chile

    Directory of Open Access Journals (Sweden)

    Adler Lomnitz, Larissa

    2002-09-01

    Full Text Available This paper describes the origin and evolution of two Chilean political parties (the Radical Party and the Christian Democrat Party through the analysis of the social networks that originated and composed them. The aim of this study is to propose a model of national political cultures on the basis of the structure of social networks related to power and of the symbol system, which legitimizes it. The structure of social networks, horizontal and vertical, are based on reciprocal or redistributive forms of exchange, on what is being exchanged and on the articulation between networks. In every society there are symmetrical and asymmetrical exchanges, which produce horizontal and vertical networks. These networks interact among themselves to form the social fabric. The dominance of some over others and how they combine, delineate the character of the political culture (authoritarian vs. egalitarian. Chile is a multiparty country within which there are cohorts of horizontal groups of friends, who informally exercise a central control over their members and create invisible boundaries setting them apart from others, in which leadership is under constrains. The result is both a strong presidential system based on an almost fanatic legitimacy, combined with factionalism and a strong parliamentary system.

  14. Social contagions on interdependent lattice networks

    Science.gov (United States)

    Shu, Panpan; Gao, Lei; Zhao, Pengcheng; Wang, Wei; Stanley, H. Eugene

    2017-03-01

    Although an increasing amount of research is being done on the dynamical processes on interdependent spatial networks, knowledge of how interdependent spatial networks influence the dynamics of social contagion in them is sparse. Here we present a novel non-Markovian social contagion model on interdependent spatial networks composed of two identical two-dimensional lattices. We compare the dynamics of social contagion on networks with different fractions of dependency links and find that the density of final recovered nodes increases as the number of dependency links is increased. We use a finite-size analysis method to identify the type of phase transition in the giant connected components (GCC) of the final adopted nodes and find that as we increase the fraction of dependency links, the phase transition switches from second-order to first-order. In strong interdependent spatial networks with abundant dependency links, increasing the fraction of initial adopted nodes can induce the switch from a first-order to second-order phase transition associated with social contagion dynamics. In networks with a small number of dependency links, the phase transition remains second-order. In addition, both the second-order and first-order phase transition points can be decreased by increasing the fraction of dependency links or the number of initially-adopted nodes.

  15. SOCIAL POLARIZATION AND CONFLICT: A NETWORK APPROACH

    Directory of Open Access Journals (Sweden)

    Ernesto Cárdenas

    2013-12-01

    Full Text Available Theoretically, polarization is associated with a higher probability of social conflict. This paper, in a microeconomic model based on the theory of social networks, analyses how changes in the network's structure affect the level of some basic parameters associated with the concept of polarization. This study shows that under upward monotonic preferences, longer sets of affiliations for each individual reduce polarization, whereas under downward monotonic preferences, longer sets of the so-called bad affiliations increase polarization. Finally, in the case of a non-monotonic system of preferences, an expansion of the affiliations set will alter the resulting polarization order in different ways depending on the preferences themselves

  16. A social network model of supply chain management in formal and informal inter-firm engagement

    Directory of Open Access Journals (Sweden)

    Lokhman Hakim Osman

    2015-12-01

    Full Text Available Background: This research looks into the different effects of firms' network structural positions in an upstream supply network upon the firms' level of relational capital outcomes.  Previous research has largely focus on the context of decentralized network structure.  However, the supply network is a centralized network because of the existence of the focal firm.  The existence of the focal firm may influence the impact of relational capital outcomes.  Methods: The objective of this research is to determine the type of network structural positions required to obtain reasonable relational capital outcome in upstream supply network.  Results and conclusions: This study found that, network structural positions i.e. betweeness centrality contributed to firms' level of relational capital influence. In conclusion, firms, embedded in upstream supply network benefits differently in terms of relational capital through different degree of embeddedness.  Firms' resources should be re-aligned to match the benefits with the different network structural positions.

  17. Towards Network Games with Social Preferences

    CERN Document Server

    Kuznetsov, Petr

    2010-01-01

    Many distributed systems can be modeled as network games: a collection of selfish players that communicate in order to maximize their individual utilities. The performance of such games can be evaluated through the costs of the system equilibria: the system states in which no player can increase her utility by unilaterally changing her behavior. However, assuming that all players are selfish and in particular that all players have the same utility function may not always be appropriate. Hence, several extensions to incorporate also altruistic and malicious behavior in addition to selfishness have been proposed over the last years. In this paper, we seek to go one step further and study arbitrary relationships between participants. In particular, we introduce the notion of the social range matrix and explore the effects of the social range matrix on the equilibria in a network game. In order to derive concrete results, we propose a simplistic network creation game that captures the effect of social relationshi...

  18. Development and Analyses of Privacy Management Models in Online Social Networks Based on Communication Privacy Management Theory

    Science.gov (United States)

    Lee, Ki Jung

    2013-01-01

    Online social networks (OSNs), while serving as an emerging means of communication, promote various issues of privacy. Users of OSNs encounter diverse occasions that lead to invasion of their privacy, e.g., published conversation, public revelation of their personally identifiable information, and open boundary of distinct social groups within…

  19. Development and Analyses of Privacy Management Models in Online Social Networks Based on Communication Privacy Management Theory

    Science.gov (United States)

    Lee, Ki Jung

    2013-01-01

    Online social networks (OSNs), while serving as an emerging means of communication, promote various issues of privacy. Users of OSNs encounter diverse occasions that lead to invasion of their privacy, e.g., published conversation, public revelation of their personally identifiable information, and open boundary of distinct social groups within…

  20. Social capital, friendship networks, and youth unemployment.

    Science.gov (United States)

    Hällsten, Martin; Edling, Christofer; Rydgren, Jens

    2017-01-01

    Youth unemployment is a contemporary social problem in many societies. Youths often have limited access to information about jobs and limited social influence, yet little is known about the relationship between social capital and unemployment risk among youth. We study the effect of social capital on unemployment risk in a sample of 19 year olds of Swedish, Iranian, and Yugoslavian origin living in Sweden (N = 1590). We distinguish between two dimensions of social capital: occupational contact networks and friendship networks. First, ego's unemployment is found to be strongly associated with friends' unemployment among individuals of Yugoslavian origins and individuals of Swedish origin, but not Iranian origin. Second, occupational contact networks reduce unemployment risks for all groups, but especially so for Iranians. The effect sizes of the two dimensions are similar and substantial: going from low to high values on these measures is associated with a difference of some 60-70 percent relative difference in unemployment risk. The findings are robust to a number of different model specifications, including a rich set of social origin controls, personality traits, educational performance, friends' characteristics, and friendship network characteristics, as well as controls for geographical employment patterns. A sensitivity simulation shows that homogeneity bias need to be very strong to explain away the effect.

  1. Purity homophily in social networks.

    Science.gov (United States)

    Dehghani, Morteza; Johnson, Kate; Hoover, Joe; Sagi, Eyal; Garten, Justin; Parmar, Niki Jitendra; Vaisey, Stephen; Iliev, Rumen; Graham, Jesse

    2016-03-01

    Does sharing moral values encourage people to connect and form communities? The importance of moral homophily (love of same) has been recognized by social scientists, but the types of moral similarities that drive this phenomenon are still unknown. Using both large-scale, observational social-media analyses and behavioral lab experiments, the authors investigated which types of moral similarities influence tie formations. Analysis of a corpus of over 700,000 tweets revealed that the distance between 2 people in a social-network can be predicted based on differences in the moral purity content-but not other moral content-of their messages. The authors replicated this finding by experimentally manipulating perceived moral difference (Study 2) and similarity (Study 3) in the lab and demonstrating that purity differences play a significant role in social distancing. These results indicate that social network processes reflect moral selection, and both online and offline differences in moral purity concerns are particularly predictive of social distance. This research is an attempt to study morality indirectly using an observational big-data study complemented with 2 confirmatory behavioral experiments carried out using traditional social-psychology methodology.

  2. Social Networking: Keeping It Clean

    Science.gov (United States)

    Waters, John K.

    2011-01-01

    The need to maintain an unpolluted learning environment is no easy task for schools and districts that have incorporated social networking sites into their educational life. The staff and teachers at Blaine High School in Minnesota's Anoka-Hennepin District 11 had been considering the pros and cons of establishing a school Facebook page when the…

  3. Privacy and Social Networking Sites

    Science.gov (United States)

    Timm, Dianne M.; Duven, Carolyn J.

    2008-01-01

    College students are relying on the Internet to make connections with other people every day. As the Internet has developed and grown, so have the capabilities for interaction. Social networking sites, a group of Web sites that provide people with the opportunity to create an online profile and to share that profile with others, are a part of…

  4. Node Classification in Social Networks

    Science.gov (United States)

    Bhagat, Smriti; Cormode, Graham; Muthukrishnan, S.

    When dealing with large graphs, such as those that arise in the context of online social networks, a subset of nodes may be labeled. These labels can indicate demographic values, interest, beliefs or other characteristics of the nodes (users). A core problem is to use this information to extend the labeling so that all nodes are assigned a label (or labels).

  5. Mining and modeling character networks

    CERN Document Server

    Bonato, Anthony; Elenberg, Ethan R; Gleich, David F; Hou, Yangyang

    2016-01-01

    We investigate social networks of characters found in cultural works such as novels and films. These character networks exhibit many of the properties of complex networks such as skewed degree distribution and community structure, but may be of relatively small order with a high multiplicity of edges. Building on recent work of beveridge, we consider graph extraction, visualization, and network statistics for three novels: Twilight by Stephanie Meyer, Steven King's The Stand, and J.K. Rowling's Harry Potter and the Goblet of Fire. Coupling with 800 character networks from films found in the http://moviegalaxies.com/ database, we compare the data sets to simulations from various stochastic complex networks models including random graphs with given expected degrees (also known as the Chung-Lu model), the configuration model, and the preferential attachment model. Using machine learning techniques based on motif (or small subgraph) counts, we determine that the Chung-Lu model best fits character networks and we ...

  6. Hierarchical social networks and information flow

    Science.gov (United States)

    López, Luis; F. F. Mendes, Jose; Sanjuán, Miguel A. F.

    2002-12-01

    Using a simple model for the information flow on social networks, we show that the traditional hierarchical topologies frequently used by companies and organizations, are poorly designed in terms of efficiency. Moreover, we prove that this type of structures are the result of the individual aim of monopolizing as much information as possible within the network. As the information is an appropriate measurement of centrality, we conclude that this kind of topology is so attractive for leaders, because the global influence each actor has within the network is completely determined by the hierarchical level occupied.

  7. GAIA - a generalizable, extensible structure for integrating games, models and social networking to support decision makers

    Science.gov (United States)

    Paxton, L. J.; Schaefer, R. K.; Nix, M.; Fountain, G. H.; Weiss, M.; Swartz, W. H.; Parker, C. L.; MacDonald, L.; Ihde, A. G.; Simpkins, S.; GAIA Team

    2011-12-01

    In this paper we describe the application of a proven methodology for modeling the complex social and economic interactions embodied in real-world decision making to water scarcity and water resources. We have developed a generalizable, extensible facility we call "GAIA" - Global Assimilation of Information for Action - and applied it to different problem sets. We describe the use of the "Green Country Model" and other gaming/simulation tools to address the impacts of climate and climate disruption issues at the intersection of science, economics, policy, and society. There is a long history in the Defense community of using what are known as strategic simulations or "wargames" to model the complex interactions between the environment, people, resources, infrastructure and the economy in a competitive environment. We describe in this paper, work that we have done on understanding how this heritage can be repurposed to help us explore how the complex interplay between climate disruption and our socio/political and economic structures will affect our future. Our focus here is on a fundamental and growing issue - water and water availability. We consider water and the role of "virtual water" in the system. Various "actors" are included in the simulations. While these simulations cannot definitively predict what will happen, they do illuminate non-linear feedbacks between, for example, treaty agreement, the environment, the economy, and the government. These simulations can be focused on the global, regional, or local environment. We note that these simulations are not "zero sum" games - there need not be a winner and a loser. They are, however, competitive influence games: they represent the tools that a nation, state, faction or group has at its disposal to influence policy (diplomacy), finances, industry (economy), infrastructure, information, etc to achieve their particular goals. As in the real world the problem is competitive - not everyone shares the same

  8. Finding Online Extremists in Social Networks

    CERN Document Server

    Klausen, Jytte; Zaman, Tauhid

    2016-01-01

    Online extremists in social networks pose a new form of threat to the general public. These extremists range from cyberbullies who harass innocent users to terrorist organizations such as the Islamic State of Iraq and Syria (ISIS) that use social networks to recruit and incite violence. Currently social networks suspend the accounts of such extremists in response to user complaints. The challenge is that these extremist users simply create new accounts and continue their activities. In this work we present a new set of operational capabilities to deal with the threat posed by online extremists in social networks. Using data from several hundred thousand extremist accounts on Twitter, we develop a behavioral model for these users, in particular what their accounts look like and who they connect with. This model is used to identify new extremist accounts by predicting if they will be suspended for extremist activity. We also use this model to track existing extremist users as they create new accounts by identif...

  9. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks.

    Science.gov (United States)

    Herrera, Mauricio; Armelini, Guillermo; Salvaj, Erica

    2015-01-01

    There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS) model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions.

  10. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks.

    Directory of Open Access Journals (Sweden)

    Mauricio Herrera

    Full Text Available There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions.

  11. Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks

    Science.gov (United States)

    2015-01-01

    There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS) model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions. PMID:26505473

  12. Social Networking: It's Not What You Think

    Science.gov (United States)

    Jones, Kevin D.

    2010-01-01

    This slide presentation reviews some of the current uses of the social networking sites available on the internet. It list some of the skills that are now considered obsolete and reviews the major social networking sites.

  13. Information spreading on dynamic social networks

    CERN Document Server

    Liu, Chuang

    2012-01-01

    Nowadays, information spreading on social networks has triggered an explosive attention in various disciplines. Most of previous related works in this area mainly focus on discussing the effects of spreading probability or immunization strategy on static networks. However, in real systems, the peer-to-peer network structure changes constantly according to frequently social activities of users. In order to capture this dynamical property and study its impact on information spreading, in this Letter, a link rewiring strategy based on the Fermi function is introduced. In the present model, the informed individuals tend to break old links and reconnect to ones with more uninformed neighbors. Simulation results on the susceptible-infected (\\textit{SI}) model with non-redundancy contacts indicate that the information spread more faster and broader with the rewiring strategy. Extensive analyses of the information cascading show that the spreading process of the initial steps plays a very important role, that is to s...

  14. Masculinity, Educational Achievement and Social Status: A Social Network Analysis

    Science.gov (United States)

    Lusher, Dean

    2011-01-01

    This study utilises a quantitative case study social network approach to explore the connection between masculinity and scholastic achievement in two secondary, all-boys schools in Australia. In both schools two social networks representing social status are explored: the "friendship" network as a measure of status that includes…

  15. 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....

  16. Status differentiation : New insights from agent-based modeling and social network analysis

    NARCIS (Netherlands)

    Grow, André

    2016-01-01

    Status is an important aspect of social life that affects people from the day they are born until the day they die. In this dissertation, André Grow examines the processes by which status inequality can emerge between individuals and between social groups, such as men/women, whites/non-whites, and t

  17. Using the forest, people, fire agent-based social network model to investigate interactions in social-ecological systems

    Science.gov (United States)

    Paige Fischer; Adam Korejwa; Jennifer Koch; Thomas Spies; Christine Olsen; Eric White; Derric Jacobs

    2013-01-01

    Wildfire links social and ecological systems in dry-forest landscapes of the United States. The management of these landscapes, however, is bifurcated by two institutional cultures that have different sets of beliefs about wildfire, motivations for managing wildfire risk, and approaches to administering policy. Fire protection, preparedness, and response agencies often...

  18. Privacy and Security: Online Social Networking

    Directory of Open Access Journals (Sweden)

    Akriti Verma, Deepak Kshirsagar, Sana Khan

    2013-03-01

    Full Text Available Online Social Networking (OSN sites such asFacebook, Twitter, Google+ attract hundreds andmillions of users. Such social networks have acentralized architecture wherein user's private dataand user generated content are centrally owned by asingle administrative domain that managescommunication between its users. As a result,centralized social networks have gatheredunprecedented amounts of data about the behaviorsand personalities of individuals, raising majorprivacy and security concerns. This has put indemand for a decentralized social networking sitethat addresses the privacy and security issues.

  19. Exploring Impact: Negative Effects of Social Networks

    OpenAIRE

    Egbert, Henrik; Sedlarski, Teodor

    2011-01-01

    he sociological literature on social networks emphasizes by and large positive network effects. Negative effects of such networks are discussed rather rarely. This paper tackles negative effects by applying economic theory, particularly neoclassical theory, new institutional theory and the results from experimental economics to the concept of social networks. In the paper it is assumed that social networks are exclusive and since exclusiveness affects the allocation of resources, negative ext...

  20. 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.

  1. Social Network Change Detection

    Science.gov (United States)

    2008-03-17

    Mathematical Statistics 16, 117-186. Wald A. (1947). Sequential Analysis, Wiley, New York. Wald , A. & Wolfowitz , J. (1948). Optimum Character of the...for exponential random graph models, Sociological Methodology, 2006, 99-153. Wald A. (1945). Sequential Tests of Statistical Hypotheses. Annals of

  2. 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…

  3. Challenges for Mobile Social Networking Applications

    Science.gov (United States)

    Rana, Juwel; Kristiansson, Johan; Hallberg, Josef; Synnes, Kåre

    This paper presents work in progress regarding utilization of social network information for mobile applications. Primarily a number of challenges are identified, such as how to mine data from multiple social networks, how to integrate and consolidate social networks, and how to manage semantic information for mobile applications. The challenges are discussed from a semantic Web perspective using a driving scenario as motivation.

  4. Compensatory fuzzy logic for intelligent social network analysis

    Directory of Open Access Journals (Sweden)

    Maikel Y. Leyva-Vázquez

    2014-10-01

    Full Text Available Fuzzy graph theory has gained in visibility for social network analysis. In this work fuzzy logic and their role in modeling social relational networks is discussed. We present a proposal for extending the fuzzy logic framework to intelligent social network analysis using the good properties of robustness and interpretability of compensatory fuzzy logic. We apply this approach to the concept path importance taking into account the length and strength of the connection. Results obtained with our model are more consistent with the way human make decisions. Additionally a case study to illustrate the applicability of the proposal on a coauthorship network is developed. Our main outcome is a new model for social network analysis based on compensatory fuzzy logic that gives more robust results and allows compensation. Moreover this approach makes emphasis in using language for social network analysis.

  5. Integration of scientific and social networks

    NARCIS (Netherlands)

    Neshati, Mahmood; Hiemstra, Djoerd; Asgari, Ehsaneddin; Beigy, Hamid

    In this paper, we address the problem of scientific-social network integration to find a matching relationship between members of these networks (i.e. The DBLP publication network and the Twitter social network). This task is a crucial step toward building a multi environment expert finding system

  6. Discrete Opinion Dynamics on Online Social Networks

    Institute of Scientific and Technical Information of China (English)

    HU Yan-Li; BAI Liang; ZHANG Wei-Ming

    2013-01-01

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

  7. Investigation of Social Studies Teachers' Intended Uses of Social Networks in Terms of Various Variables

    Science.gov (United States)

    Akgün, Ismail Hakan

    2016-01-01

    The aim of this research is to determine Social Studies teacher candidates' intended uses of social networks in terms of various variables. The research was carried out by using screening model of quantitative research methods. In the study, "The Social Network Intended Use Scale" was used as a data collection tool. As a result of the…

  8. Nuevos modelos de comunicación, perfiles y tendencias en las redes sociales New Models of Communication, Profiles and Trends in Social Networks

    Directory of Open Access Journals (Sweden)

    Jesús Miguel Flores Vivar

    2009-10-01

    Full Text Available Las redes sociales en línea se han convertido en el estandarte de la Web 2.0, entorno que también aglutina a los blogs, wikis y chats. Existe una fina división entre una red social, un blog y un wiki. Hablar de redes sociales es referirnos al siguiente estadio de Internet, como en su momento fueron los blogs. Se han constituido en un fenómeno de masas cada vez más importante tanto así que ya algunas están integrando plataformas de blogs y wikis en una sola interfaz. Pero, ¿qué nuevas formas de comunicación y de negocio subyacen en las redes?, ¿qué perfiles profesionales se necesitan para esta nueva audiencia?, ¿deben los medios crear redes o adaptarse a los nuevos entornos de donde emerge un nuevo periodismo basado en la participación? El presente artículo intenta responder a estas y otras variables. Social networks have become the banner of Web 2.0, which also hosts blogs, wikis and chats. There is a slight dividing line between a social network, a blog and a wiki. Talking about social networks means referring to the next stage of the Internet, as talking about blogs once did. Internet social networks have become an increasingly important phenomenon because some platforms are integrating blogs and wikis on a single interface. But we could ask what new types of communication and business lie beneath these networks; what professional profiles are needed for this new audience. Should media create the networks, or just adapt to the new environments, whence a new journalism based on participation emerges? This paper tries to answer these and other questions.

  9. 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.

  10. Web Mining and Social Networking

    DEFF Research Database (Denmark)

    Xu, Guandong; Zhang, Yanchun; Li, Lin

    This book examines the techniques and applications involved in the Web Mining, Web Personalization and Recommendation and Web Community Analysis domains, including a detailed presentation of the principles, developed algorithms, and systems of the research in these areas. The applications of web ...... sense of individuals or communities. The volume will benefit both academic and industry communities interested in the techniques and applications of web search, web data management, web mining and web knowledge discovery, as well as web community and social network analysis....

  11. When business networks “kill” social networks

    DEFF Research Database (Denmark)

    Jackson, Laurel; Young, L.

    2016-01-01

    that considers the changes to a community's social network and the associated norms emerging from the growing influence of a microfinance providers' network. A case study reports the impact of microfinance on a particular Bangladesh rural community. We show there is a breakdown in traditional social networks......Social networks are a key contributor to the economic and social fabric of life. There is evidence that the social cohesion that social networks provide is critical for societies to prosper economically and for development to be sustainable. These social networks and the functions they perform co......-exist with, influence and are influenced by the business networks of connected firms and other economic organisations that surround them. This is increasingly so in our ever-more-complex, internationalized and connected world. This paper explores the potential consequences of this influence via a case study...

  12. Social Networking Sites: A premise on enhancement

    Directory of Open Access Journals (Sweden)

    MANINDERPAL SINGH SAINI

    2013-12-01

    Full Text Available This article address five constructs that are paramount toward continued evolution of social networking sites (SNS`s they include, - stabilisation, visual, language, security and flexibility. These constructs add to our proposed framework. Firmly grounded research on social networking sites and literature, we propose that user feedback, is the critical component that stimulates the development and growth of social networking sites online. We offer a framework that can aid new and current social networking sites toward success. We conclude that the management of social networking sites should be treated as a process that is pragmatic and paradoxically, be stimulated.

  13. 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

  14. Integration of Communication and Social Network Modeling Platforms using ELICIT and the Wireless Emulation Laboratory

    Science.gov (United States)

    2011-06-01

    exploration and exploitation,” Administrative Science Quarterly 14. J. Diesner, T. Frantz, K. Carley, “Communication Networks from the Enron Email...Corpus, "It’s Always About the People. Enron is no Different".” Computational and Mathematical Organization Theory, 11, 201-228, 2005. 52 (December

  15. 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.

  16. Using Social Network Research in HRM

    DEFF Research Database (Denmark)

    Kaše, Robert; King, Zella; Minbaeva, Dana

    2013-01-01

    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......; 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....

  17. Point-Process Models of Social Network Interactions: Parameter Estimation and Missing Data Recovery

    Science.gov (United States)

    2014-08-01

    valid OMB control number. 1. REPORT DATE AUG 2014 2. REPORT TYPE 3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE Point-process...the remainder, emphasising the need for robust access controls . Future work should address how network structure impacts the ability to fill in missing...25] Ogata , Y. 1981 On Lewis’ simulation method for point processes. IEEE Transactions on Information Theory 27, 23–31. [26] — 1998 Space-time point

  18. Dynamical and bursty interactions in social networks

    CERN Document Server

    Stehle, Juliette; Bianconi, Ginestra

    2010-01-01

    We present a modeling framework for dynamical and bursty contact networks made of agents in social interaction. We consider agents' behavior at short time scales, in which the contact network is formed by disconnected cliques of different sizes. At each time a random agent can make a transition from being isolated to being part of a group, or vice-versa. Different distributions of contact times and inter-contact times between individuals are obtained by considering transition probabilities with memory effects, i.e. the transition probabilities for each agent depend both on its state (isolated or interacting) and on the time elapsed since the last change of state. The model lends itself to analytical and numerical investigations. The modeling framework can be easily extended, and paves the way for systematic investigations of dynamical processes occurring on rapidly evolving dynamical networks, such as the propagation of an information, or spreading of diseases.

  19. Detecting Change in Longitudinal Social Networks

    Science.gov (United States)

    2011-01-01

    marketing campaigns and media on social behavior. Initial Construct populations, social and knowledge networks, can be hypothetical or real (Carley...patent data bases, phone-networks, email- based-networks, social- media networks and more. Page 6 of 37 Current methods of change detection in...CUSUM C Sta measured fo o be successf Average Bet ct either incre or each socia g increases in the data for fective for ch ork. tistic Over Tim

  20. Analyzing negative ties in social networks

    OpenAIRE

    Mankirat Kaur; Sarbjeet Singh

    2016-01-01

    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 i...

  1. Bayesian estimation of the network autocorrelation model

    NARCIS (Netherlands)

    Dittrich, D.; Leenders, R.T.A.J.; Mulder, J.

    2017-01-01

    The network autocorrelation model has been extensively used by researchers interested modeling social influence effects in social networks. The most common inferential method in the model is classical maximum likelihood estimation. This approach, however, has known problems such as negative bias of

  2. Unfavorable Individuals in Social Gaming Networks

    Science.gov (United States)

    Zhang, Yichao; Chen, Guanrong; Guan, Jihong; Zhang, Zhongzhi; Zhou, Shuigeng

    2015-12-01

    In social gaming networks, the current research focus has been on the origin of widespread reciprocal behaviors when individuals play non-cooperative games. In this paper, we investigate the topological properties of unfavorable individuals in evolutionary games. The unfavorable individuals are defined as the individuals gaining the lowest average payoff in a round of game. Since the average payoff is normally considered as a measure of fitness, the unfavorable individuals are very likely to be eliminated or change their strategy updating rules from a Darwinian perspective. Considering that humans can hardly adopt a unified strategy to play with their neighbors, we propose a divide-and-conquer game model, where individuals can interact with their neighbors in the network with appropriate strategies. We test and compare a series of highly rational strategy updating rules. In the tested scenarios, our analytical and simulation results surprisingly reveal that the less-connected individuals in degree-heterogeneous networks are more likely to become the unfavorable individuals. Our finding suggests that the connectivity of individuals as a social capital fundamentally changes the gaming environment. Our model, therefore, provides a theoretical framework for further understanding the social gaming networks.

  3. Matching Community Structure Across Online Social Networks

    OpenAIRE

    Lin LI; Campbell, W. M.

    2016-01-01

    The discovery of community structure in networks is a problem of considerable interest in recent years. In online social networks, often times, users are simultaneously involved in multiple social media sites, some of which share common social relationships. It is of great interest to uncover a shared community structure across these networks. However, in reality, users typically identify themselves with different usernames across social media sites. This creates a great difficulty in detecti...

  4. Predicting Group Evolution in the Social Network

    OpenAIRE

    Bródka, Piotr; Kazienko, Przemysław; Kołoszczyk, Bartosz

    2012-01-01

    Groups - social communities are important components of entire societies, analysed by means of the social network concept. Their immanent feature is continuous evolution over time. If we know how groups in the social network has evolved we can use this information and try to predict the next step in the given group evolution. In the paper, a new aproach for group evolution prediction is presented and examined. Experimental studies on four evolving social networks revealed that (i) the predict...

  5. Degree correlations in signed social networks

    Science.gov (United States)

    Ciotti, Valerio; Bianconi, Ginestra; Capocci, Andrea; Colaiori, Francesca; Panzarasa, Pietro

    2015-03-01

    We investigate degree correlations in two online social networks where users are connected through different types of links. We find that, while subnetworks in which links have a positive connotation, such as endorsement and trust, are characterized by assortative mixing by degree, networks in which links have a negative connotation, such as disapproval and distrust, are characterized by disassortative patterns. We introduce a class of simple theoretical models to analyze the interplay between network topology and the superimposed structure based on the sign of links. Results uncover the conditions that underpin the emergence of the patterns observed in the data, namely the assortativity of positive subnetworks and the disassortativity of negative ones. We discuss the implications of our study for the analysis of signed complex networks.

  6. Degree correlations in signed social networks

    CERN Document Server

    Ciotti, Valerio; Capocci, Andrea; Colaiori, Francesca; Panzarasa, Pietro

    2014-01-01

    We investigate degree correlations in two online social networks where users are connected through different types of links. We find that, while subnetworks in which links have a positive connotation, such as endorsement and trust, are characterized by assortative mixing by degree, networks in which links have a negative connotation, such as disapproval and distrust, are characterized by disassortative patterns. We introduce a class of simple theoretical models to analyze the interplay between network topology and the superimposed structure based on the sign of links. Results uncover the conditions that underpin the emergence of the patterns observed in the data, namely the assortativity of positive subnetworks and the disassortativity of negative ones. We discuss the implications of our study for the analysis of signed complex networks.

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

    Science.gov (United States)

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

    2014-01-01

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

  8. Improving Student Engagement Using Course-Based Social Networks

    Science.gov (United States)

    Imlawi, Jehad Mohammad

    2013-01-01

    This study proposes an engagement model that supports use of course-based online social networks for engaging student, and hence, improving their educational outcomes. This research demonstrates that instructors who create course-based online social networks to communicate with students can increase the student engagement in these online social…

  9. Potential of Social Networking Sites for Distance Education Student Engagement

    Science.gov (United States)

    Lester, Jaime; Perini, Michael

    2010-01-01

    This chapter explores the potential of social networking sites for increasing student engagement for distance education learners. The authors present a modified student engagement model with a focus on the integration of technology, specifically social networking sites for community college distance education learners. The chapter concludes with…

  10. Potential of Social Networking Sites for Distance Education Student Engagement

    Science.gov (United States)

    Lester, Jaime; Perini, Michael

    2010-01-01

    This chapter explores the potential of social networking sites for increasing student engagement for distance education learners. The authors present a modified student engagement model with a focus on the integration of technology, specifically social networking sites for community college distance education learners. The chapter concludes with…

  11. An Organizational Framework of Personal Health Records for Social Networks

    Science.gov (United States)

    Hasan, Syed Omair

    2009-01-01

    This work proposes an organizational framework for creating a community to share personal health record (PHR) information in the form of a Health Records Social Network (HRSN). The work builds upon existing social network community concepts as well as the existing Systemized Nomenclature of Medicine (SNOMED) model used by the medical community and…

  12. Improving Student Engagement Using Course-Based Social Networks

    Science.gov (United States)

    Imlawi, Jehad Mohammad

    2013-01-01

    This study proposes an engagement model that supports use of course-based online social networks for engaging student, and hence, improving their educational outcomes. This research demonstrates that instructors who create course-based online social networks to communicate with students can increase the student engagement in these online social…

  13. Methodological novelties applied to the anthropology of food: agent-based models and social networks analysis

    Directory of Open Access Journals (Sweden)

    Diego Díaz Córdova

    2016-12-01

    Full Text Available En este artículo presentamos dos modalidades metodológicas que aún no han sido muy utilizadas en la antropología alimentaria. Por un lado, nos referimos al análisis de redes sociales y, por otro, a los modelos basados en agentes. Para ilustrar los métodos, tomaremos dos casos de materiales clásicos de la antropología alimentaria. Para el primero usaremos los platos de comida de un relevamiento hecho en la Quebrada de Humahuaca (provincia de Jujuy, Argentina y, para el segundo, utilizaremos algunos elementos del concepto aplicado por Aguirre de “estrategias domésticas de consumo”. La idea subyacente es que, dado que la alimentación se reconoce como un “hecho social total” y, por lo tanto, como un fenómeno complejo, el abordaje metodológico debe seguir necesariamente esa misma característica. Mientras más métodos utilicemos (con el grado de rigor adecuado mejor estaremos preparados para comprender la dinámica alimentaria en el medio social.

  14. SOCIAL NETWORK ANALYSIS FOR ASSESSING SOCIAL CAPITAL IN BIOSECURITY ECOLITERACY

    Directory of Open Access Journals (Sweden)

    Sang Putu Kaler Surata

    2016-02-01

    Full Text Available Abstract: Social Network Analysis for Assessing Social Capital in Biosecurity Ecoliteracy. Biosecurity ecoliteracy (BEL is a view of literacy that applies ecological concepts to promote in-depth understanding, critical reflection, creative thinking, self consciousness, communication and social skills, in analyzing and managing issues around plant health/living, animal health/living and the risks that are associated with the environment. We used social network analysis (SNA to evaluate two distinct forms of social capital of BEL: social cohesion and network structure. This study was executed by employing cooperative learning in BEL toward 30 undergraduate teacher training students. Data then was analyzed using UCINET software. We found the tendency of so­cial cohesion to increase after students participated in BEL. This was supported by several SNA measures (density, closeness and degree and these values at the end were statistically different than at the beginning of BEL. The social structure map (sociogram after BEL visualized that students were much more likely to cluster in groups compared with the sociogram before BEL. Thus BEL, through cooperative learning, was able to promote social capital. In addition SNA proved a useful tool for evaluating the achievement levels of social capital of BEL in the form of network cohesion and network structure. Abstrak: Analisis Jaringan Sosial untuk Menilai Ekoliterasi Ketahanan Hayati. Ekoliterasi ketahanan hayati (EKH adalah literasi yang mengaplikasikan berbagai konsep ekologi untuk mempromosikan pe­mahaman yang mendalam, refleksi kritis, kesadaran diri, keterampilan sosial dan berkomunikasi, dalam menganalisis, dan mengelola isu yang terkait dengan kesehatan/kehidupan tanaman, kesehatan/kehidupan binatang, dan risiko yang terkait dengan lingkungan. Analisis jaringan kerja sosial (AJS telah digunakan untuk mengevaluasi dua bentuk model sosial EKH: kohesi sosial dan struktur jaringan kerja. Untuk itu

  15. Social networks as journalistic paradigm

    Directory of Open Access Journals (Sweden)

    José Manuel Noguera Vivo, Ph. D

    2010-01-01

    Full Text Available Spain is one of the countries with higher use of social networks in the world. Among them, Facebook is emerging as one of the most significant internationally. If these phenomena are combined with the current transformation of journalism, it is not surprising that some Spanish cybermedia have approached this platform to develop new products for the Web. From this starting point, this article focuses on the recent performances of Spanish cybermedia within social networks, specifically Facebook, with an exploratory study about both the use of native media of Web and media from the print newspapers. This research studies the use of most important Spanish cybermedia from a structured observation. Data are collected through a content analysis with an ad hoc questionnaire. The results point out few cybermedia which seem to take advantage of these networks in terms of participation. This allows us to conclude that we are in a young state of relations on the Web, where spaces and resources are not optimized.

  16. Social network extraction and analysis based on multimodal dyadic interaction.

    Science.gov (United States)

    Escalera, Sergio; Baró, Xavier; Vitrià, Jordi; Radeva, Petia; Raducanu, Bogdan

    2012-01-01

    Social interactions are a very important component in people's lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Times' Blogging Heads opinion blog. The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The links' weights are a measure of the "influence" a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network.

  17. Social Network Extraction and Analysis Based on Multimodal Dyadic Interaction

    Directory of Open Access Journals (Sweden)

    Bogdan Raducanu

    2012-02-01

    Full Text Available Social interactions are a very important component in people’s lives. Social network analysis has become a common technique used to model and quantify the properties of social interactions. In this paper, we propose an integrated framework to explore the characteristics of a social network extracted from multimodal dyadic interactions. For our study, we used a set of videos belonging to New York Times’ Blogging Heads opinion blog. The Social Network is represented as an oriented graph, whose directed links are determined by the Influence Model. The links’ weights are a measure of the “influence” a person has over the other. The states of the Influence Model encode automatically extracted audio/visual features from our videos using state-of-the art algorithms. Our results are reported in terms of accuracy of audio/visual data fusion for speaker segmentation and centrality measures used to characterize the extracted social network.

  18. Community evolution mining and analysis in social network

    Science.gov (United States)

    Liu, Hongtao; Tian, Yuan; Liu, Xueyan; Jian, Jie

    2017-03-01

    With the development of digital and network technology, various social platforms emerge. These social platforms have greatly facilitated access to information, attracting more and more users. They use these social platforms every day to work, study and communicate, so every moment social platforms are generating massive amounts of data. These data can often be modeled as complex networks, making large-scale social network analysis possible. In this paper, the existing evolution classification model of community has been improved based on community evolution relationship over time in dynamic social network, and the Evolution-Tree structure is proposed which can show the whole life cycle of the community more clearly. The comparative test result shows that the improved model can excavate the evolution relationship of the community well.

  19. 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.

  20. Social encounter networks: characterizing Great Britain.

    Science.gov (United States)

    Danon, Leon; Read, Jonathan M; House, Thomas A; Vernon, Matthew C; Keeling, Matt J

    2013-08-22

    A major goal of infectious disease epidemiology is to understand and predict the spread of infections within human populations, with the intention of better informing decisions regarding control and intervention. However, the development of fully mechanistic models of transmission requires a quantitative understanding of social interactions and collective properties of social networks. We performed a cross-sectional study of the social contacts on given days for more than 5000 respondents in England, Scotland and Wales, through postal and online survey methods. The survey was designed to elicit detailed and previously unreported measures of the immediate social network of participants relevant to infection spread. Here, we describe individual-level contact patterns, focusing on the range of heterogeneity observed and discuss the correlations between contact patterns and other socio-demographic factors. We find that the distribution of the number of contacts approximates a power-law distribution, but postulate that total contact time (which has a shorter-tailed distribution) is more epidemiologically relevant. We observe that children, public-sector and healthcare workers have the highest number of total contact hours and are therefore most likely to catch and transmit infectious disease. Our study also quantifies the transitive connections made between an individual's contacts (or clustering); this is a key structural characteristic of social networks with important implications for disease transmission and control efficacy. Respondents' networks exhibit high levels of clustering, which varies across social settings and increases with duration, frequency of contact and distance from home. Finally, we discuss the implications of these findings for the transmission and control of pathogens spread through close contact.

  1. Methodological novelties applied to the anthropology of food: agent-based models and social networks analysis

    OpenAIRE

    Diego Díaz Córdova

    2016-01-01

    En este artículo presentamos dos modalidades metodológicas que aún no han sido muy utilizadas en la antropología alimentaria. Por un lado, nos referimos al análisis de redes sociales y, por otro, a los modelos basados en agentes. Para ilustrar los métodos, tomaremos dos casos de materiales clásicos de la antropología alimentaria. Para el primero usaremos los platos de comida de un relevamiento hecho en la Quebrada de Humahuaca (provincia de Jujuy, Argentina) y, para el segundo, utilizaremos a...

  2. Location Privacy Protection on Social Networks

    Science.gov (United States)

    Zhan, Justin; Fang, Xing

    Location information is considered as private in many scenarios. Protecting location information on mobile ad-hoc networks has attracted much research in past years. However, location information protection on social networks has not been paid much attention. In this paper, we present a novel location privacy protection approach on the basis of user messages in social networks. Our approach grants flexibility to users by offering them multiple protecting options. To the best of our knowledge, this is the first attempt to protect social network users' location information via text messages. We propose five algorithms for location privacy protection on social networks.

  3. 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.

  4. Will Learning Social Inclusion Assist Rural Networks

    Science.gov (United States)

    Marchant, Jillian

    2013-01-01

    Current research on social networks in some rural communities reports continuing demise despite efforts to build resilient communities. Several factors are identified as contributing to social decline including globalisation and rural social characteristics. Particular rural social characteristics, such as strong social bonds among members of…

  5. Will Learning Social Inclusion Assist Rural Networks

    Science.gov (United States)

    Marchant, Jillian

    2013-01-01

    Current research on social networks in some rural communities reports continuing demise despite efforts to build resilient communities. Several factors are identified as contributing to social decline including globalisation and rural social characteristics. Particular rural social characteristics, such as strong social bonds among members of…

  6. Understanding Members’ Attachment to Social Networking Sites

    DEFF Research Database (Denmark)

    Lim, Eric T. K.; Cyr, Dianne; Tan, Chee-Wee

    2014-01-01

    Social Networking Sites (SNSs) are pervasive phenomena in today’s society. With greater connectivity and interactivity enabled through emerging technologies, SNSs provide communication platforms for individuals to bridge spatial and temporal differences when making friends, sharing experiences...... and competitive mentality towards others within SNSs. We further construct a theoretical model of members’ communal attachments within SNSs that is then empirically validated via an online survey of 787 active members of SNSs. Empirical findings suggest that members’ communal attachments play an instrumental role...

  7. Mobile Social Network in a Cultural Context

    DEFF Research Database (Denmark)

    Liu, Jun

    2010-01-01

    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...... contributes to the explosive growth of the message within mobile social networks under special circumstances, such as during festivals and holidays and social disturbances. This circulation in turn increases both the dissemination and credibility of messages, and rumours. The characteristics and strength...

  8. A Computer Network for Social Scientists.

    Science.gov (United States)

    Gerber, Barry

    1989-01-01

    Describes a microcomputer-based network developed at the University of California Los Angeles to support education in the social sciences. Topics discussed include technological, managerial, and academic considerations of university networking; the use of the network in teaching macroeconomics, social demographics, and symbolic logic; and possible…

  9. Computational social networks security and privacy

    CERN Document Server

    2012-01-01

    Presents the latest advances in security and privacy issues in computational social networks, and illustrates how both organizations and individuals can be protected from real-world threats Discusses the design and use of a wide range of computational tools and software for social network analysis Provides experience reports, survey articles, and intelligence techniques and theories relating to specific problems in network technology

  10. Trust transitivity in social networks

    CERN Document Server

    Richters, Oliver

    2010-01-01

    Non-centralized recommendation-based decision making is a central feature of several social and technological processes, such as market dynamics, peer-to-peer file-sharing and the web of trust of digital certification. We investigate the properties of trust propagation on networks, based on a simple metric of trust transitivity. We investigate analytically the percolation properties of trust transitivity in random networks with arbitrary degree distribution, and compare with numerical realizations. We find that the existence of a non-zero fraction of absolute trust (i.e. entirely confident trust) is a requirement for the viability of global trust propagation in large systems: The average pair-wise trust is marked by a discontinuous transition at a specific fraction of absolute trust, below which it vanishes. Furthermore, we perform an extensive analysis of the Pretty Good Privacy (PGP) web of trust, in view of the concepts introduced. We compare different scenarios of trust distribution: community- and author...

  11. 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).

  12. Recent developments in exponential random graph (p*) models for social networks

    NARCIS (Netherlands)

    Robins, Garry; Snijders, Tom; Wang, Peng; Handcock, Mark; Pattison, Philippa

    2007-01-01

    This article reviews new specifications for exponential random graph models proposed by Snijders et al. [Snijders, T.A.B., Pattison, P., Robins, G.L., Handcock, M., 2006. New specifications for exponential random graph models. Sociological Methodology] and demonstrates their improvement over homogen

  13. Profit Mechanisms and Business Models for Social Networks%社会网络中盈利机制和业务模型研究

    Institute of Scientific and Technical Information of China (English)

    汤婧; 蔡敏敏; 王玉峰

    2014-01-01

    基于社会网络的几种主要盈利机制(广告、增值服务、交易费),受双边市场理论的启发,提出了社会网络的业务模型;针对社交网络的特点,提出了基于双边市场的用户参与的激励模型,以期能更好地激励用户参与社交网络应用。%In this paper, we summarize the main profit generators of social networks:advertising, value-added services, and transaction fees. Inspired by the two-sided market theory, we propose a formal business model for social networking applications. Depending on the characteristic of the social network, we propose an incentive model to motivate users to use social network applications.

  14. Privacy in Online Social Networking Sites

    Directory of Open Access Journals (Sweden)

    M.Ida Evones

    2015-11-01

    Full Text Available There are more than 192 act ive social networking websites. Bringing every kind of social group together in one place and letting them interact is really a big thing indeed .Huge amount of information process in the sites each day, end up making it vulnerable to attack. There is no systematic framework taking into account the importance of privacy. Increased privacy settings don’t always guarantee privacy when there is a loop hole in the applications. Lack of user education results is over sharing. Privacy settings to limit access to some data are available, but these settings are never the default. Only a tiny minority make use of these. Online social network does not provide any demarcation line between private and public information. The personal informat ion shared in online social networks can harm the user in often unexpected ways. Private data is available in plenty. The major privacy problems are due to complicated privacy model, implementation errors and economic pressure. Until recently, not much work was done in this area. The recent papers, which I have collected is a Testimony to state that lot of work needs to be done in this area.

  15. Networked Learning in Networks: infrastructures for social learning & distributed innovation

    NARCIS (Netherlands)

    Sloep, Peter

    2011-01-01

    Sloep, P. B. (2011, 1-3 September). Networked Learning in Networks: infrastructures for social learning & distributed innovation. Presentation at the Third International Conference on Software, Services and Semantic Technologies (S3T 2011), Bourgas, Bulgaria.

  16. Information Diffusion and Provenance in Online Social Media Networks

    Directory of Open Access Journals (Sweden)

    Naman Goel

    2013-06-01

    Full Text Available Traditional data mining techniques are going through an extensive research so as to suit their application in the dynamically evolving social media networks which are not only large in size but also require real time processing of data streams. One such application which is of social, industrial and political interest is to maximize (sometimes even minimize information diffusion in online social media networks. Word-of-mouth (w-o-m communications have been largely employed in a wide range of application scenarios ranging from marketing strategies to creating mass awareness. In recent years, we saw an explosion in the growth of online social networks with many successful service providers like Facebook, twitter,YouTube, LinkedIn etc. ruling the market. The use of online social networks is not limited to fun and building professional networks. Online social networks are now seen as a powerful medium to effect the social and political environment of a country and the world as a whole. Information on these social networking sites sometimes needs to be propagated very effectively and quickly to fulfill the concerned strategies. It is equally important that given some information present on social network, we are able to derive its origin so that rumours can be distinguished from truth. In this paper, we discuss some of the issues and challenges in information diffusion and provenance from online social networks point of view. We also discuss some of the approaches and models that have been used for information diffusion and provenance in online social networks in recent past. Some of these approaches have been evaluated by researchers for specific social network services but we will discuss them in a general sense.

  17. Social networks in cardiovascular disease management.

    Science.gov (United States)

    Shaya, Fadia T; Yan, Xia; Farshid, Maryam; Barakat, Samer; Jung, Miah; Low, Sara; Fedder, Donald

    2010-12-01

    Cardiovascular disease remains the leading cause of death in the USA. Social networks have a positive association with obesity, smoking cessation and weight loss. This article summarizes studies evaluating the impact of social networks on the management of cardiovascular disease. The 35 studies included in the article describe the impact of social networks on a decreased incidence of cardiovascular disease, depression and mortality. In addition, having a large-sized social network is also associated with better outcomes and improved health. The role of pharmacists is beginning to play an important role in the patient-centered medical home, which needs to be incorporated into social networks. The patient-centered medical home can serve as an adaptive source for social network evolvement.

  18. Matching Community Structure Across Online Social Networks

    CERN Document Server

    Li, Lin

    2016-01-01

    The discovery of community structure in networks is a problem of considerable interest in recent years. In online social networks, often times, users are simultaneously involved in multiple social media sites, some of which share common social relationships. It is of great interest to uncover a shared community structure across these networks. However, in reality, users typically identify themselves with different usernames across social media sites. This creates a great difficulty in detecting the community structure. In this paper, we explore several approaches for community detection across online social networks with limited knowledge of username alignment across the networks. We refer to the known alignment of usernames as seeds. We investigate strategies for seed selection and its impact on networks with a different fraction of overlapping vertices. The goal is to study the interplay between network topologies and seed selection strategies, and to understand how it affects the detected community structu...

  19. Social networking technology, social network composition, and reductions in substance use among homeless adolescents.

    Science.gov (United States)

    Rice, Eric; Milburn, Norweeta G; Monro, William

    2011-03-01

    Peer-based prevention programs for homeless youth are complicated by the potential for reinforcing high-risk behaviors among participants. The goal of this study is to understand how homeless youth could be linked to positive peers in prevention programming by understanding where in social and physical space positive peers for homeless youth are located, how these ties are associated with substance use, and the role of social networking technologies (e.g., internet and cell phones) in this process. Personal social network data were collected from 136 homeless adolescents in Los Angeles, CA. Respondents reported on composition of their social networks with respect to: home-based peers and parents (accessed via social networking technology; e.g., the internet, cell phone, texting), homeless peers and agency staff (accessed face-to-face) and whether or not network members were substance-using or non-substance-using. Associations between respondent's lifetime cocaine, heroin, and methamphetamine use and recent (previous 30 days) alcohol and marijuana use were assessed by the number of non-substance-using versus substance-using ties in multivariate linear regression models. 43% of adolescents reported a non-substance-using home-based tie. More of these ties were associated with less recent alcohol use. 62% of adolescents reported a substance-using homeless tie. More of these ties were associated with more recent marijuana use as well as more lifetime heroin and methamphetamine use. For homeless youth, who are physically disconnected from positive peers, social networking technologies can be used to facilitate the sorts of positive social ties that effective peer-based prevention programs require.

  20. Weighted social networks for a large scale artificial society

    Science.gov (United States)

    Fan, Zong Chen; Duan, Wei; Zhang, Peng; Qiu, Xiao Gang

    2016-12-01

    The method of artificial society has provided a powerful way to study and explain how individual behaviors at micro level give rise to the emergence of global social phenomenon. It also creates the need for an appropriate representation of social structure which usually has a significant influence on human behaviors. It has been widely acknowledged that social networks are the main paradigm to describe social structure and reflect social relationships within a population. To generate social networks for a population of interest, considering physical distance and social distance among people, we propose a generation model of social networks for a large-scale artificial society based on human choice behavior theory under the principle of random utility maximization. As a premise, we first build an artificial society through constructing a synthetic population with a series of attributes in line with the statistical (census) data for Beijing. Then the generation model is applied to assign social relationships to each individual in the synthetic population. Compared with previous empirical findings, the results show that our model can reproduce the general characteristics of social networks, such as high clustering coefficient, significant community structure and small-world property. Our model can also be extended to a larger social micro-simulation as an input initial. It will facilitate to research and predict some social phenomenon or issues, for example, epidemic transition and rumor spreading.

  1. Improving Family Forest Knowledge Transfer through Social Network Analysis

    Science.gov (United States)

    Gorczyca, Erika L.; Lyons, Patrick W.; Leahy, Jessica E.; Johnson, Teresa R.; Straub, Crista L.

    2012-01-01

    To better engage Maine's family forest landowners our study used social network analysis: a computational social science method for identifying stakeholders, evaluating models of engagement, and targeting areas for enhanced partnerships. Interviews with researchers associated with a research center were conducted to identify how social network…

  2. Exploring Self-Disclosure in Online Social Networks

    Science.gov (United States)

    Velasco-Martin, Javier

    2013-01-01

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

  3. CONNECTIONS USING SOCIAL NETWORKS AND SOCIAL INTELLIGENCE OF STUDENTS

    Directory of Open Access Journals (Sweden)

    Belma Duvnjak

    2013-05-01

    Full Text Available Social intelligence is the ability and skills to cope with everyday life situations and how to cope with interpersonal relationships. Today's generation of relationships based, carried and nurtured through various social networks. The aim of the presented research is to identify the impact of social networks on the development of social intelligence. The study was done on a sample, which makes the 208 students from the Faculty of Education at the University "Džemal Bijedić" in Mostar. The results show that the impact of social networks on the development of positive social intelligence. Greater achievement on tests of social intelligence (SI were significantly correlated with the amount of time spent using different social networks.

  4. SHARING KNOWLEDGE INSIDE SOCIAL NETWORK SITES

    Directory of Open Access Journals (Sweden)

    Georgeta DRUL

    2009-12-01

    Full Text Available The virtual communities are increasingly numerous. The understanding of virtual community structure, functionalities and dynamics show us how to act in the sense of practice and in the benefit of organization and own person. The practice directions are creation the communities of practice, the virtual collaboration, and knowledge management. The purpose of this paper is to identify a model of a virtual community used in Romania and the activities in the social networks sites that are important to generate knowledge and information sharing and to develop new relationships, as well. (2 The research outcomes provided on a model used in the virtual community show us whether knowledge sharing has a support in the reality. One of the objectives of this paper is to verify that the intense activities in communities equates with knowledge sharing. This paper presents a comparative analysis of social networks sites, the most commonly used in the Romanian space: Hi5, MySpace, FaceBook and LinkedIn. The study uses several independent input variables and follows as output two factors: sharing knowledge and developing new relationships in the virtual community. The input variables are: information identifying the person and degree of trust in the social network site and in the community members. The information identifying the person suggests the relationship public – private, different self presentation styles and the identification of behaviour in cyberspace.

  5. A User Perspective on Social Networking Sites

    DEFF Research Database (Denmark)

    Sørensen, Lene Tolstrup; Porras, Jari; Hajikhani, Arash

    2014-01-01

    For years, social media have been a part of daily life. Within the last 5-10 years, the use of social media (and in particular social networking sites) has expanded to almost all sides of life: private people, businesses and public institutions. This paper presents an overview of different uses...... of social networks to give a picture of the variety in use. The paper describes differences in private persons’ use of social networking sites, different business purposes, and how social networking sites can challenge public administrations. Throughout the paper there are provided small cases...... and situations where the social networking sites have been used in a remarkable way. The paper is made in collaboration between partners in the World Wide Research Forum....

  6. Role of Security in Social Networking

    Directory of Open Access Journals (Sweden)

    David Hiatt

    2016-02-01

    Full Text Available In this paper, the concept of security and privacy in social media, or social networking will be discussed. First, a brief history and the concept of social networking will be introduced. Many of the security risks associated with using social media are presented. Also, the issue of privacy and how it relates to security are described. Based on these discussions, some solutions to improve a user’s privacy and security on social networks will be suggested. Our research will help the readers to understand the security and privacy issues for the social network users, and some steps which can be taken by both users and social network organizations to help improve security and privacy.

  7. A User Perspective on Social Networking Sites

    DEFF Research Database (Denmark)

    Sørensen, Lene Tolstrup; Porras, Jari; Hajikhani, Arash

    2014-01-01

    For years, social media have been a part of daily life. Within the last 5-10 years, the use of social media (and in particular social networking sites) has expanded to almost all sides of life: private people, businesses and public institutions. This paper presents an overview of different uses...... of social networks to give a picture of the variety in use. The paper describes differences in private persons’ use of social networking sites, different business purposes, and how social networking sites can challenge public administrations. Throughout the paper there are provided small cases...... and situations where the social networking sites have been used in a remarkable way. The paper is made in collaboration between partners in the World Wide Research Forum....

  8. SOCIAL NETWORK EFFECTS ON ROMANTIC RELATIONSHIP

    OpenAIRE

    Can, Fatma; Selim HOVARDAOGLU

    2015-01-01

    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 app...

  9. 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...comScore, GlobalWebIndex, Alexa, and financial reports for the parent companies of the social networking tools. The subsequent list includes global... company websites and financial reports. LinkedIn does not provide a monthly active user number, but it reports 300 million regis- tered users. Because

  10. Discovering Mobile Social Networks by Semantic Technologies

    Science.gov (United States)

    Jung, Jason J.; Choi, Kwang Sun; Park, Sung Hyuk

    It has been important for telecommunication companies to discover social networks from mobile subscribers. They have attempted to provide a number of recommendation services, but they realized that the services were not successful. In this chapter, we present semantic technologies for discovering social networks. The process is mainly composed of two steps; (1) profile identification and (2) context understanding. Through developing a Next generation Contents dElivery (NICE) platform, we were able to generate various services based on the discovered social networks.

  11. Group Evolution Discovery in Social Networks

    OpenAIRE

    Bródka, Piotr; Saganowski, Stanisław; Kazienko, Przemysław

    2013-01-01

    Group extraction and their evolution are among the topics which arouse the greatest interest in the domain of social network analysis. However, while the grouping methods in social networks are developed very dynamically, the methods of group evolution discovery and analysis are still uncharted territory on the social network analysis map. Therefore the new method for the group evolution discovery called GED is proposed in this paper. Additionally, the results of the first experiments on the ...

  12. A Dynamic Algebraic Specification for Social Networks

    CERN Document Server

    Ksystra, Katerina; Triantafyllou, Nikolaos; Stefaneas, Petros

    2011-01-01

    With the help of the Internet, social networks have grown rapidly. This has increased security requirements. We present a formalization of social networks as composite behavioral objects, defined using the Observational Transition System (OTS) approach. Our definition is then translated to the OTS/CafeOBJ algebraic specification methodology. This translation allows the formal verification of safety properties for social networks via the Proof Score method. Finally, using this methodology we formally verify some security properties.

  13. The Strategic Paradox of Social Networks

    Science.gov (United States)

    2011-03-18

    cause long-lasting effects. For example, a recent Career Builder survey found the number of civilian employers who used social networking sites as...Service members discussing political subjects on social networking sites can quickly attract negative attention. In March 2010, Marine Corps Sergeant...on social networking sites . In March 2010, stories surfaced reporting the Israeli army canceled a mission after a soldier “disclosed the name of the

  14. Polarity related influence maximization in signed social networks.

    Directory of Open Access Journals (Sweden)

    Dong Li

    Full Text Available Influence maximization in social networks has been widely studied motivated by applications like spread of ideas or innovations in a network and viral marketing of products. Current studies focus almost exclusively on unsigned social networks containing only positive relationships (e.g. friend or trust between users. Influence maximization in signed social networks containing both positive relationships and negative relationships (e.g. foe or distrust between users is still a challenging problem that has not been studied. Thus, in this paper, we propose the polarity-related influence maximization (PRIM problem which aims to find the seed node set with maximum positive influence or maximum negative influence in signed social networks. To address the PRIM problem, we first extend the standard Independent Cascade (IC model to the signed social networks and propose a Polarity-related Independent Cascade (named IC-P diffusion model. We prove that the influence function of the PRIM problem under the IC-P model is monotonic and submodular Thus, a greedy algorithm can be used to achieve an approximation ratio of 1-1/e for solving the PRIM problem in signed social networks. Experimental results on two signed social network datasets, Epinions and Slashdot, validate that our approximation algorithm for solving the PRIM problem outperforms state-of-the-art methods.

  15. Polarity related influence maximization in signed social networks.

    Science.gov (United States)

    Li, Dong; Xu, Zhi-Ming; Chakraborty, Nilanjan; Gupta, Anika; Sycara, Katia; Li, Sheng

    2014-01-01

    Influence maximization in social networks has been widely studied motivated by applications like spread of ideas or innovations in a network and viral marketing of products. Current studies focus almost exclusively on unsigned social networks containing only positive relationships (e.g. friend or trust) between users. Influence maximization in signed social networks containing both positive relationships and negative relationships (e.g. foe or distrust) between users is still a challenging problem that has not been studied. Thus, in this paper, we propose the polarity-related influence maximization (PRIM) problem which aims to find the seed node set with maximum positive influence or maximum negative influence in signed social networks. To address the PRIM problem, we first extend the standard Independent Cascade (IC) model to the signed social networks and propose a Polarity-related Independent Cascade (named IC-P) diffusion model. We prove that the influence function of the PRIM problem under the IC-P model is monotonic and submodular Thus, a greedy algorithm can be used to achieve an approximation ratio of 1-1/e for solving the PRIM problem in signed social networks. Experimental results on two signed social network datasets, Epinions and Slashdot, validate that our approximation algorithm for solving the PRIM problem outperforms state-of-the-art methods.

  16. Two models of social learning in networks, with concepts drawn from economics and physics

    Science.gov (United States)

    Chatterjee, Kalyan; Roy, Souvik

    2016-12-01

    In this paper, we consider the status of economics as a science, especially as compared to the most successful of sciences, physics, and formulate this in terms of the Popperian notion of criticisability (an extension of his earlier falsifiability demarcation criterion between science and other studies). We then discuss how methods having some similarity to models prevalent in physics might help elucidate dynamic analyses of heuristic learning in economics, though each of the two felds has a unique conceptual framework.

  17. Individual Differences as Predictors of Social Networking

    National Research Council Canada - National Science Library

    Orchard, Lisa J; Fullwood, Chris; Galbraith, Niall; Morris, Neil

    2014-01-01

    Research suggests that personality dictates specific Internet preferences. One area that remains relatively unexplored is the influence of personality on engagement with social networking sites ( SNSs...

  18. 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.

  19. The Social Side of Information Networking.

    Science.gov (United States)

    Katz, James E.

    1997-01-01

    Explores the social issues, including manners, security, crime (fraud), and social control associated with information networking, with emphasis on the Internet. Also addresses the influence of cellular phones, the Internet and other information technologies on society. (GR)

  20. Node discovery problem for a social network

    CERN Document Server

    Maeno, Yoshiharu

    2007-01-01

    This paper presents a practical heuristic algorithm to address a node discovery problem. The node discovery problem is to discover a clue on the person, who does not appear in the observed records, but is relevant functionally in affecting decision-making and behavior of an organization. We define two topological relevance of a node in a social network (global and local relevance). Association between the topological relevance and the functional relevance is studied with a few example networks in criminal organizations. We propose a heuristic algorithm to infer an invisible, functionally relevant person. Its performance (precision, recall, and F value) is demonstrated with a simulation experiment using a network derived from the Watts-Strogatz (WS) model.

  1. 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.

  2. MODELS FOR NETWORK DYNAMICS - A MARKOVIAN FRAMEWORK

    NARCIS (Netherlands)

    LEENDERS, RTAJ

    1995-01-01

    A question not very often addressed in social network analysis relates to network dynamics and focuses on how networks arise and change. It alludes to the idea that ties do not arise or vanish randomly, but (partly) as a consequence of human behavior and preferences. Statistical models for modeling

  3. Social network and lifestyle in Danish adults

    DEFF Research Database (Denmark)

    Osler, Merete

    1995-01-01

    Analyzed associations between 2,987 adults' social networks and lifestyles in terms of leisure activity, smoking, and the intake of vegetables. Compared with socially integrated men, those with few social contacts or little social support were more often inactive during leisure time and did not e...... health related behaviors. (PsycINFO Database Record (c) 2012 APA, all rights reserved)...

  4. Brain and Social Networks: Fundamental Building Blocks of Human Experience.

    Science.gov (United States)

    Falk, Emily B; Bassett, Danielle S

    2017-09-01

    How do brains shape social networks, and how do social ties shape the brain? Social networks are complex webs by which ideas spread among people. Brains comprise webs by which information is processed and transmitted among neural units. While brain activity and structure offer biological mechanisms for human behaviors, social networks offer external inducers or modulators of those behaviors. Together, these two axes represent fundamental contributors to human experience. Integrating foundational knowledge from social and developmental psychology and sociology on how individuals function within dyads, groups, and societies with recent advances in network neuroscience can offer new insights into both domains. Here, we use the example of how ideas and behaviors spread to illustrate the potential of multilayer network models. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Predicting Anchor Links between Heterogeneous Social Networks

    CERN Document Server

    Sajadmanesh, Sina; Khodadadi, Ali

    2016-01-01

    People usually get involved in multiple social networks to enjoy new services or to fulfill their needs. Many new social networks try to attract users of other existing networks to increase the number of their users. Once a user (called source user) of a social network (called source network) joins a new social network (called target network), a new inter-network link (called anchor link) is formed between the source and target networks. In this paper, we concentrated on predicting the formation of such anchor links between heterogeneous social networks. Unlike conventional link prediction problems in which the formation of a link between two existing users within a single network is predicted, in anchor link prediction, the target user is missing and will be added to the target network once the anchor link is created. To solve this problem, we use meta-paths as a powerful tool for utilizing heterogeneous information in both the source and target networks. To this end, we propose an effective general meta-pat...

  6. Network Simulation Models

    Science.gov (United States)

    2008-12-01

    well, then a Euclidean distance would be appropriate. The quadratic assignment procedure ( QAP ) (Krackhardt, 1987) could be used to compare the...Networks. Journal of Applied Psychology, 71(1): 50-55. Krackhardt, D. (1987). QAP Partialling as a Test of Spuriousness. Social Networks, 9, 171-186

  7. 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.

  8. Mobile Social Network in a Cultural Context

    DEFF Research Database (Denmark)

    Liu, Jun

    2010-01-01

    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......, 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....

  9. 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.

  10. SOCIAL NETWORK ANALYSIS IN AN ONLINE BLOGOSPHERE

    Directory of Open Access Journals (Sweden)

    DR. M. MOHAMED SATHIK

    2011-01-01

    Full Text Available Social network is a social structure that exists among the similar interest of individuals, organizations or even on relations like friendship. Social network analysis is the measure of relationship between people, organizations and processing entities. In today’s scenario, Internet is acting as an interface for the people who spread across the globe to exchange their ideas. Social network analysis is a Web 2.0 application, which facilitates the users tointeract, response and express their views. Social network analysis has greatest attention as a research area in computer science in the recent past. Blogs or weblogs are like catalogs that are maintained by individuals related to a particular topic of interest. In this problem, we analyze the blog responses as social networks that are posted by AIDS patients over a period of time.

  11. Social selection and peer influence in an online social network.

    Science.gov (United States)

    Lewis, Kevin; Gonzalez, Marco; Kaufman, Jason

    2012-01-03

    Disentangling the effects of selection and influence is one of social science's greatest unsolved puzzles: Do people befriend others who are similar to them, or do they become more similar to their friends over time? Recent advances in stochastic actor-based modeling, combined with self-reported data on a popular online social network site, allow us to address this question with a greater degree of precision than has heretofore been possible. Using data on the Facebook activity of a cohort of college students over 4 years, we find that students who share certain tastes in music and in movies, but not in books, are significantly likely to befriend one another. Meanwhile, we find little evidence for the diffusion of tastes among Facebook friends-except for tastes in classical/jazz music. These findings shed light on the mechanisms responsible for observed network homogeneity; provide a statistically rigorous assessment of the coevolution of cultural tastes and social relationships; and suggest important qualifications to our understanding of both homophily and contagion as generic social processes.

  12. Visualization of Influencing Nodes in Online Social Networks

    Directory of Open Access Journals (Sweden)

    Prajit Limsaiprom

    2014-04-01

    Full Text Available The rise of the Internet accelerates the creation of various large-scale online social networks. The online social networks have brought considerable attention as an important medium for the information diffusion model, which can be described the relationships and activities among human beings. The online social networks’ relationships in the real world are too big to present with useful information to identify the criminal or cyber attacks. The methodology for information security analysis was proposed with the complementary of Cluster Algorithm and Social Network Analysis, which presented anomaly and cyber attack patterns in online social networks and visualized the influencing nodes of such anomaly and cyber attacks. The closet vertices of influencing nodes could not avoid from the harmfulness in social networking. The new proposed information security analysis methodology and results were significance analysis and could be applied as a guide for further investigate of social network behavior to improve the security model and notify the risk, computer viruses or cyber attacks for online social networks in advance.

  13. 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%.

  14. 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%.

  15. Power to Detect Intervention Effects on Ensembles of Social Networks

    Science.gov (United States)

    Sweet, Tracy M.; Junker, Brian W.

    2016-01-01

    The hierarchical network model (HNM) is a framework introduced by Sweet, Thomas, and Junker for modeling interventions and other covariate effects on ensembles of social networks, such as what would be found in randomized controlled trials in education research. In this article, we develop calculations for the power to detect an intervention…

  16. CNEM: Cluster Based Network Evolution Model

    Directory of Open Access Journals (Sweden)

    Sarwat Nizamani

    2015-01-01

    Full Text Available This paper presents a network evolution model, which is based on the clustering approach. The proposed approach depicts the network evolution, which demonstrates the network formation from individual nodes to fully evolved network. An agglomerative hierarchical clustering method is applied for the evolution of network. In the paper, we present three case studies which show the evolution of the networks from the scratch. These case studies include: terrorist network of 9/11 incidents, terrorist network of WMD (Weapons Mass Destruction plot against France and a network of tweets discussing a topic. The network of 9/11 is also used for evaluation, using other social network analysis methods which show that the clusters created using the proposed model of network evolution are of good quality, thus the proposed method can be used by law enforcement agencies in order to further investigate the criminal networks

  17. Emotion shapes the diffusion of moralized content in social networks.

    Science.gov (United States)

    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.

  18. Evolution of Cooperation in Adaptive Social Networks

    Science.gov (United States)

    Segbroeck, Sven Van; Santos, Francisco C.; Traulsen, Arne; Lenaerts, Tom; Pacheco, Jorge M.

    Humans are organized in societies, a phenomenon that would never have been possible without the evolution of cooperative behavior. Several mechanisms that foster this evolution have been unraveled over the years, with population structure as a prominent promoter of cooperation. Modern networks of exchange and cooperation are, however, becoming increasingly volatile, and less and less based on long-term stable structure. Here, we address how this change of paradigm aspects the evolution of cooperation. We discuss analytical and numerical models in which individuals can break social ties and create new ones. Interactions are modeled as two-player dilemmas of cooperation. Once a link between two individuals has formed, the productivity of this link is evaluated. Links can be broken off at different rates. This individual capacity of forming new links or severing inconvenient ones can effectively change the nature of the game. We address random formation of new links and local linking rules as well as different individual capacities to maintain social interactions. We conclude by discussing how adaptive social networks can become an important step towards more realistic models of cultural dynamics.

  19. 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.

  20. 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

  1. Predicting Positive and Negative Links in Online Social Networks

    CERN Document Server

    Leskovec, Jure; Kleinberg, Jon

    2010-01-01

    We study online social networks in which relationships can be either positive (indicating relations such as friendship) or negative (indicating relations such as opposition or antagonism). Such a mix of positive and negative links arise in a variety of online settings; we study datasets from Epinions, Slashdot and Wikipedia. We find that the signs of links in the underlying social networks can be predicted with high accuracy, using models that generalize across this diverse range of sites. These models provide insight into some of the fundamental principles that drive the formation of signed links in networks, shedding light on theories of balance and status from social psychology; they also suggest social computing applications by which the attitude of one user toward another can be estimated from evidence provided by their relationships with other members of the surrounding social network.

  2. Going Social: The Impact of Social Networking in Promoting Education

    Science.gov (United States)

    Jain, Neelesh Kumar; Verma, Ashish; Verma, Rama Shankar; Tiwari, Prashant

    2012-01-01

    The growth and the popularity of the Social networks has a high impact on the development of the students in the field of Personality, Attitudes, Knowledge and on its whole academic performance in classroom and society. This paper envisage on the impact of Social Network on Education and Training of the students.

  3. 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…

  4. 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…

  5. Web Mining and Social Networking

    DEFF Research Database (Denmark)

    Xu, Guandong; Zhang, Yanchun; Li, Lin

    sense of individuals or communities. The volume will benefit both academic and industry communities interested in the techniques and applications of web search, web data management, web mining and web knowledge discovery, as well as web community and social network analysis.......This book examines the techniques and applications involved in the Web Mining, Web Personalization and Recommendation and Web Community Analysis domains, including a detailed presentation of the principles, developed algorithms, and systems of the research in these areas. The applications of web...... mining, and the issue of how to incorporate web mining into web personalization and recommendation systems are also reviewed. Additionally, the volume explores web community mining and analysis to find the structural, organizational and temporal developments of web communities and reveal the societal...

  6. Construction of Learning Model Based on Social Knowledge Network%基于社会性知识网络的学习模型构建

    Institute of Scientific and Technical Information of China (English)

    段金菊; 余胜泉

    2016-01-01

    在各种新的学习理论和学习技术的支持下,社会化学习尤其是社会性知识网络作为一种新的在线学习理念,有助于解决当前在线教育面临的诸多问题,逐渐引起研究者的重视。社会性知识网络是知识网络和社会网络的聚合体,承载了社会化学习的特点,是一种基于知识的社会性分享、社会性协作、社会性贡献和社会性创造而形成的社会网络。社会性知识网络研究的首要核心问题是如何构建学习模型,以揭示社会化学习发生和发展的机制并指导实践。以社会性知识网络的知识观和学习观以及社会化学习的一般模型为依据,基于社会性知识网络的学习模型可概括为一条设计主线、两类学习隐喻、三条基本原则和四个核心要素。其中,一条设计主线是指以学习者为中心构建个人学习网络以促进社会化学习;两类学习隐喻是指学习的网络联通隐喻和创造隐喻;三条基本原则是指基于交互活动的社会化参与原则,基于学习者中心的知识贡献和创造原则,基于知识网络与社会网络双重视角的学习联结原则。四个核心要素是指学习者角色、内容单元、交互行为和社会性知识网络环境。%Supported by a variety of new learning theory and learning technology, social learning especially social knowledge network becomes a new online learning idea, which helps to solve many learning problems for current online education, and has attracted more and more attention from many researchers. Meanwhile, social knowledge network integrates knowledge network with social network, which is a social network based on social knowledge sharing, social knowledge cooperation, social knowledge contribution and social knowledge creation. Currently, the first key problem of the research into social knowledge network is how to construct a learning model, with the aim to reveal the mechanism of the

  7. Rumor Diffusion in an Interests-Based Dynamic Social Network

    Directory of Open Access Journals (Sweden)

    Mingsheng Tang

    2013-01-01

    Full Text Available To research rumor diffusion in social friend network, based on interests, a dynamic friend network is proposed, which has the characteristics of clustering and community, and a diffusion model is also proposed. With this friend network and rumor diffusion model, based on the zombie-city model, some simulation experiments to analyze the characteristics of rumor diffusion in social friend networks have been conducted. The results show some interesting observations: (1 positive information may evolve to become a rumor through the diffusion process that people may modify the information by word of mouth; (2 with the same average degree, a random social network has a smaller clustering coefficient and is more beneficial for rumor diffusion than the dynamic friend network; (3 a rumor is spread more widely in a social network with a smaller global clustering coefficient than in a social network with a larger global clustering coefficient; and (4 a network with a smaller clustering coefficient has a larger efficiency.

  8. 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.

  9. Dynamic Network Models

    CERN Document Server

    Armbruster, Benjamin

    2011-01-01

    We analyze random networks that change over time. First we analyze a dynamic Erdos-Renyi model, whose edges change over time. We describe its stationary distribution, its convergence thereto, and the SI contact process on the network, which has relevance for connectivity and the spread of infections. Second, we analyze the effect of node turnover, when nodes enter and leave the network, which has relevance for network models incorporating births, deaths, aging, and other demographic factors.

  10. 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...

  11. Science, Society, and Social Networking

    Science.gov (United States)

    White, K. S.; Lohwater, T.

    2009-12-01

    The increased use of social networking is changing the way that scientific societies interact with their members and others. The American Association for the Advancement of Science (AAAS) uses a variety of online networks to engage its members and the broader scientific community. AAAS members and non-members can interact with AAAS staff and each other on AAAS sites on Facebook, YouTube, and Twitter, as well as blogs and forums on the AAAS website (www.aaas.org). These tools allow scientists to more readily become engaged in policy by providing information on current science policy topics as well as methods of involvement. For example, members and the public can comment on policy-relevant stories from Science magazine’s ScienceInsider blog, download a weekly policy podcast, receive a weekly email update of policy issues affecting the scientific community, or watch a congressional hearing from their computer. AAAS resource websites and outreach programs, including Communicating Science (www.aaas.org/communicatingscience), Working with Congress (www.aaas.org/spp/cstc/) and Science Careers (http://sciencecareers.sciencemag.org) also provide tools for scientists to become more personally engaged in communicating their findings and involved in the policy process.

  12. Social networks, social support mechanisms, and quality of life after breast cancer diagnosis.

    Science.gov (United States)

    Kroenke, Candyce H; Kwan, Marilyn L; Neugut, Alfred I; Ergas, Isaac J; Wright, Jaime D; Caan, Bette J; Hershman, Dawn; Kushi, Lawrence H

    2013-06-01

    We examined mechanisms through which social relationships influence quality of life (QOL) in breast cancer survivors. This study included 3,139 women from the Pathways Study who were diagnosed with breast cancer from 2006 to 2011 and provided data on social networks (the presence of a spouse or intimate partner, religious/social ties, volunteering, and numbers of close friends and relatives), social support (tangible support, emotional/informational support, affection, positive social interaction), and QOL, measured by the FACT-B, approximately 2 months post diagnosis. We used logistic models to evaluate associations between social network size, social support, and lower versus higher than median QOL scores. We further stratified by stage at diagnosis and treatment. In multivariate-adjusted analyses, women who were characterized as socially isolated had significantly lower FACT-B (OR = 2.18, 95 % CI: 1.72-2.77), physical well-being (WB) (OR = 1.61, 95 % CI: 1.27-2.03), functional WB (OR = 2.08, 95 % CI: 1.65-2.63), social WB (OR = 3.46, 95 % CI: 2.73-4.39), and emotional WB (OR = 1.67, 95 % CI: 1.33-2.11) scores and higher breast cancer symptoms (OR = 1.48, 95 % CI: 1.18-1.87) compared with socially integrated women. Each social network member independently predicted higher QOL. Simultaneous adjustment for social networks and social support partially attenuated associations between social networks and QOL. The strongest mediator and type of social support that was most predictive of QOL outcomes was "positive social interaction." However, each type of support was important depending on outcome, stage, and treatment status. Larger social networks and greater social support were related to higher QOL after a diagnosis of breast cancer. Effective social support interventions need to evolve beyond social-emotional interventions and need to account for disease severity and treatment status.

  13. Competition between global and local online social networks.

    Science.gov (United States)

    Kleineberg, Kaj-Kolja; Boguñá, Marián

    2016-04-27

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

  14. Competition between global and local online social networks

    Science.gov (United States)

    Kleineberg, Kaj-Kolja; Boguñá, Marián

    2016-04-01

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

  15. Enhancing Classroom Effectiveness through Social Networking Tools

    Science.gov (United States)

    Kurthakoti, Raghu; Boostrom, Robert E., Jr.; Summey, John H.; Campbell, David A.

    2013-01-01

    To determine the usefulness of social networking Web sites such as Ning.com as a communication tool in marketing courses, a study was designed with special concern for social network use in comparison to Blackboard. Students from multiple marketing courses were surveyed. Assessments of Ning.com and Blackboard were performed both to understand how…

  16. Mapping social networks in software process improvement

    DEFF Research Database (Denmark)

    Tjørnehøj, Gitte; Nielsen, Peter Axel

    2005-01-01

    to map social networks and suggest how it can be used in software process improvement. We applied the mapping approach in a small software company to support the realization of new ways of improving software processes. The mapping approach was found useful in improving social networks, and thus furthers...

  17. Social Networks: Gated Communities or Free Cantons?

    CERN Document Server

    CERN. Geneva

    2017-01-01

    Online social networks and other cloud-based services have concentrated the control of the web in the hands of a few corporations. Our personal data has been commodified, often without our knowledge or consent. Is there a way to retain all the benefits of social networking without giving up control of our data?

  18. 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…

  19. Social networking sites and adolescent health.

    Science.gov (United States)

    Moreno, Megan A; Kolb, Jennifer

    2012-06-01

    Social networking sites are popular among and consistently used by adolescents. These sites present benefits as well as risks to adolescent health. Recently, pediatric providers have also considered the benefits and risks of using social networking sites in their own practices.

  20. Entrepreneurial Idea Identification through Online Social Networks

    Science.gov (United States)

    Lang, Matthew C.

    2010-01-01

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