Social network architecture and the maintenance of deleterious cultural traits.

How have changes in communications technology affected the way that misinformation spreads through a population and persists? To what extent do differences in the architecture of social networks affect the spread of misinformation, relative to the rates and rules by which individuals transmit or eliminate different pieces of information (cultural traits)? Here, we use analytical models and individual-based simulations to study how a 'cultural load' of misinformation can be maintained in a population under a balance between social transmission and selective elimination of cultural traits with low intrinsic value. While considerable research has explored how network architecture affects percolation processes, we find that the relative rates at which individuals transmit or eliminate traits can have much more profound impacts on the cultural load than differences in network architecture. In particular, the cultural load is insensitive to correlations between an individual's network degree and rate of elimination when these quantities vary among individuals. Taken together, these results suggest that changes in communications technology may have influenced cultural evolution more strongly through changes in the amount of information flow, rather than the details of who is connected to whom.

Information sharing and social network dynamics : a coevolutionary approach

The capacity to interact socially and share information underlies the success of many animal species, humans included. Researchers of many fields have emphasized the evo¬lutionary significance of how patterns of connections between individuals, or the social networks, and learning abilities affect the information obtained by animal societies. To date, studies have focused on the dynamics either of social networks, or of the spread of information. The present work aims to study them together. We make use of mathematical and computational models to study the dynamics of networks, where social learning and information sharing affect the structure of the population the individuals belong to. The number and strength of the relationships between individuals, in turn, impact the accessibility and the diffusion of the shared information. Moreover, we inves¬tigate how different strategies in the evaluation and choice of interacting partners impact the processes of knowledge acquisition and social structure rearrangement. First, we look at how different evaluations of social interactions affect the availability of the information and the network topology. We compare a first case, where individuals evaluate social exchanges by the amount of information that can be shared by the partner, with a second case, where they evaluate interactions by considering their partners' social status. We show that, even if both strategies take into account the knowledge endowments of the partners, they have very different effects on the system. In particular, we find that the first case generally enables individuals to accumulate higher amounts of information, thanks to the more efficient patterns of social connections they are able to build. Then, we study the effects that homophily, or the tendency to interact with similar partners, has on knowledge accumulation and social structure. We compare the case where individuals who know the same information are more likely to learn socially from each other, to the opposite case, where individuals who know different information are instead more likely to learn socially from each other. We find that it is not trivial to claim which strategy is better than the other. Depending on the possibility of forgetting information, the way new social partners can be chosen, and the population size, we delineate the conditions for which each strategy allows accumulating more information, or in a faster way For these conditions, we also discuss the topological characteristics of the resulting social structure, relating them to the information dynamics outcome. In conclusion, this work paves the road for modeling the joint dynamics of the spread of information among individuals and their social interactions. It also provides a formal framework to study jointly the effects of different strategies in the choice of partners on social structure, and how they favor the accumulation of knowledge in the population. - La capacité d'interagir socialement et de partager des informations est à la base de la réussite de nombreuses espèces animales, y compris les humains. Les chercheurs de nombreux domaines ont souligné l'importance évolutive de la façon dont les modes de connexions entre individus, ou réseaux sociaux et les capacités d'apprentissage affectent les informations obtenues par les sociétés animales. À ce jour, les études se sont concentrées sur la dynamique soit des réseaux sociaux, soit de la diffusion de l'information. Le présent travail a pour but de les étudier ensemble. Nous utilisons des modèles mathématiques et informatiques pour étudier la dynamique des réseaux, où l'apprentissage social et le partage d'information affectent la structure de la population à laquelle les individus appartiennent. Le nombre et la solidité des relations entre les individus ont à leurs tours un impact sur l'accessibilité et la diffusion de l'informa¬tion partagée. Par ailleurs, nous étudions comment les différentes stratégies d'évaluation et de choix des partenaires d'interaction ont une incidence sur les processus d'acquisition des connaissances ainsi que le réarrangement de la structure sociale. Tout d'abord, nous examinons comment des évaluations différentes des interactions sociales influent sur la disponibilité de l'information ainsi que sur la topologie du réseau. Nous comparons un premier cas, où les individus évaluent les échanges sociaux par la quantité d'information qui peut être partagée par le partenaire, avec un second cas, où ils évaluent les interactions en tenant compte du statut social de leurs partenaires. Nous montrons que, même si les deux stratégies prennent en compte le montant de connaissances des partenaires, elles ont des effets très différents sur le système. En particulier, nous constatons que le premier cas permet généralement aux individus d'accumuler de plus grandes quantités d'information, grâce à des modèles de connexions sociales plus efficaces qu'ils sont capables de construire. Ensuite, nous étudions les effets que l'homophilie, ou la tendance à interagir avec des partenaires similaires, a sur l'accumulation des connaissances et la structure sociale. Nous comparons le cas où des personnes qui connaissent les mêmes informations sont plus sus¬ceptibles d'apprendre socialement l'une de l'autre, au cas où les individus qui connaissent des informations différentes sont au contraire plus susceptibles d'apprendre socialement l'un de l'autre. Nous constatons qu'il n'est pas trivial de déterminer quelle stratégie est meilleure que l'autre. En fonction de la possibilité d'oublier l'information, la façon dont les nouveaux partenaires sociaux peuvent être choisis, et la taille de la population, nous déterminons les conditions pour lesquelles chaque stratégie permet d'accumuler plus d'in¬formations, ou d'une manière plus rapide. Pour ces conditions, nous discutons également les caractéristiques topologiques de la structure sociale qui en résulte, les reliant au résultat de la dynamique de l'information. En conclusion, ce travail ouvre la route pour la modélisation de la dynamique conjointe de la diffusion de l'information entre les individus et leurs interactions sociales. Il fournit également un cadre formel pour étudier conjointement les effets de différentes stratégies de choix des partenaires sur la structure sociale et comment elles favorisent l'accumulation de connaissances dans la population.

APTIC : a social network to improve the quality of life of members of patients' associations

Peer-reviewed

Social network extraction and analysis based on multimodal dyadic interaction

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.

A Social Network Analysis of Twitter: Mapping the Digital Humanities Community

Defining digital humanities might be an endless debate if we stick to the discussion about the boundaries of this concept as an academic "discipline". In an attempt to concretely identify this field and its actors, this paper shows that it is possible to analyse them through Twitter, a social media widely used by this "community of practice". Based on a network analysis of 2,500 users identified as members of this movement, the visualisation of the "who's following who?" graph allows us to highlight the structure of the network's relationships, and identify users whose position is particular. Specifically, we show that linguistic groups are key factors to explain clustering within a network whose characteristics look similar to a small world.

Comparative analysis of different meat traceability systems using multiple criteria and a social network approach

The adoption of a proper traceability system is being incorporated into meat production practices as a method of gaining consumer confidence. The various partners operating in the chain of meat production can be considered a social network, and they have the common goal of generating a communication process that can ensure each characteristic of the product, including safety. This study aimed to select the most appropriate meat traceability system “from farm to fork” that could be applied to Brazilian beef and pork production for international trade. The research was done in three steps. The first used the analytical hierarchy process (AHP) for selecting the best on-farm livestock traceability. In the second step, the actors in the meat production chain were identified to build a framework and defined each role in the network. In the third step, the selection of the traceability system was done. Results indicated that with an electronic traceability system, it is possible to acquire better connections between the links in the chain and to provide the means for managing uncertainties by creating structures that facilitate information flow more efficiently.

Understanding Online Game Players' Post-adoption Behavior: an Investigation of Social Network Games in China

Retaining players and re-attracting switching players has long been a central topic for SNG providers with regard to the post-adoption stage of playing an online game. However, there has not been much research which has explored players’ post-adoption behavior by incorporating the continuance intention and the switching intention. In addition, traditional IS continuance theories were mainly developed to investigate users’ continued use of utilitarian IS, and thus they may fall short when trying to explain the continued use of hedonic IS. Furthermore, compared to the richer literature on IS continuance, far too little attention has been paid to IS switching, leading to a dearth of knowledge on the subject, despite the increased incidence of the switching phenomenon in the IS field. By addressing the limitations of prior literature, this study seeks to examine the determinants of SNG players’ two different post-adoption behaviors, including the continuance intention and the switching intention. This study takes a positivist approach and uses survey research method to test five proposed research models based on Unified Theory of Acceptance and Use of Technology 2; Use and Gratification Theory; Push-Pull-Mooring model; Cognitive Dissonance Theory; and a self-developed model respectively with empirical data collected from the SNG players of one of the biggest SNG providers in China. A total of 3919 valid responses and 541 valid responses were used to examine the continuance intention and the switching intention, respectively. SEM is utilized as the data analysis method. The proposed research models are supported by the empirical data. The continuance intention is determined by enjoyment, fantasy, escapism, social interaction, social presence, social influence, achievement and habit. The switching intention is determined by enjoyment, satisfaction, subjective norms, descriptive norms, alternative attractiveness, the need for variety, change experience, and adaptation cost. This study contributes to IS theories in three important ways. Firstly, it shows IS switching should be included in IS post-adoption research together with IS continuance. Secondly, a modern IS is usually multi-functional and SNG players have multiple reasons for using a SNG, thus a player’s beliefs about the hedonic, social and utilitarian perceptions of their continued use of the SNG exert significant effects on the continuance intention. Thirdly, the determinants of the switch ing intention mainly exert push, pull, and mooring effects. Players’ beliefs about their current SNG and the available alternatives, as well as their individual characteristics are all significant determinants of the switching intention. SNG players combine these effects in order to formulate the switching intention. Finally, this study presents limitations and suggestions for future research.

Towards a Privacy-enhanced Social Networking Site

L’avénement des réseaux sociaux, tel que Facebook, MySpace et LinkedIn, a fourni une plateforme permettant aux individus de rester facilement connectés avec leurs amis, leurs familles ou encore leurs collègues tout en les encourageant activement à partager leurs données personnelles à travers le réseau. Avec la richesse des activités disponibles sur un réseau social, la quantité et la variété des informations personnelles partagées sont considérables. De plus, de part leur nature numérique, ces informations peuvent être facilement copiées, modifiées ou divulguées sans le consentement explicite de leur propriétaire. Ainsi, l’information personnelle révélée par les réseaux sociaux peut affecter de manière concrète la vie de leurs utilisateurs avec des risques pour leur vie privée allant d’un simple embarras à la ruine complète de leur réputation, en passant par l’usurpation d’identité. Malheureusement, la plupart des utilisateurs ne sont pas conscients de ces risques et les outils mis en place par les réseaux sociaux actuels ne sont pas suffisants pour protéger efficacement la vie privée de leurs utilisateurs. En outre, même si un utilisateur peut contrôler l’accès à son propre profil, il ne peut pas contrôler ce que les autres révèlent à son sujet. En effet, les “amis” d’un utilisateur sur un réseau social peuvent parfois révéler plus d’information à son propos que celui-ci ne le souhaiterait. Le respect de la vie privée est un droit fondamental pour chaque individu. Nous pré- sentons dans cette thèse une approche qui vise à accroître la prise de conscience des utilisateurs des risques par rapport à leur vie privée et à maintenir la souveraineté sur leurs données lorsqu’ils utilisent un réseau social. La première contribution de cette thèse réside dans la classification des risques multiples ainsi que les atteintes à la vie privée des utilisateurs d’un réseau social. Nous introduisons ensuite un cadre formel pour le respect de la vie privée dans les réseaux sociaux ainsi que le concept de politique de vie privée (UPP). Celle-ci définie par l’utilisateur offre une manière simple et flexible de spécifier et communiquer leur attentes en terme de respect de la vie privée à d’autres utilisateurs, tiers parties ainsi qu’au fournisseur du réseau social. Par ailleurs, nous dé- finissons une taxonomie (possiblement non-exhaustive) des critères qu’un réseau social peut intégrer dans sa conception pour améliorer le respect de la vie privée. En introduisant le concept de réseau social respectueux de la vie privée (PSNS), nous proposons Privacy Watch, un réseau social respectueux de la vie privée qui combine les concepts de provenance et d’imputabilité afin d’aider les utilisateurs à maintenir la souveraineté sur leurs données personnelles. Finalement, nous décrivons et comparons les différentes propositions de réseaux sociaux respectueux de la vie privée qui ont émergé récemment. Nous classifions aussi ces différentes approches au regard des critères de respect de la vie privée introduits dans cette thèse.

Social network measures for "nosduocentered" networks, their predictive power on performance

Our purpose in this article is to define a network structure which is based on two egos instead of the egocentered (one ego) or the complete network (n egos). We describe the characteristics and properties for this kind of network which we call “nosduocentered network”, comparing it with complete and egocentered networks. The key point for this kind of network is that relations exist between the two main egos and all alters, but relations among others are not observed. After that, we use new social network measures adapted to the nosduocentered network, some of which are based on measures for complete networks such as degree, betweenness, closeness centrality or density, while some others are tailormade for nosduocentered networks. We specify three regression models to predict research performance of PhD students based on these social network measures for different networks such as advice, collaboration, emotional support and trust. Data used are from Slovenian PhD students and their s

Renssellaer Institute. Jim Hendler. CSCI 4964/COMM 49652 – Web Science. Social Network

Social Networks on the World Wide Web - lecture by Dr. Jennifer Golbeck

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 4: Social Network Analysis

What are fundamental entities in social networks and what information is contained in social graphs? We will discuss some selected concepts in social network analysis, such as one- and two mode networks, prestige and centrality, and cliques, clans and clubs. Readings: Web tool predicts election results and stock prices, J. Palmer, New Scientist, 07 February (2008) [Protected Access] Optional: Social Network Analysis, Methods and Applications, S. Wasserman and K. Faust (1994)

Research on Social Network Sites

A bibliography of research on Social Network web sites. The research contained below is focused specifically on social network sites (or "social networking" sites). Some of this is connected to social media, social software, Web2.0, social bookmarking, educational technologies, communities research, etc. but this is not the organizing focus and not everything related to these other topics is included here. This list is not methodologically or disciplinarily organized. There is work here from communications, information science, anthropology, sociology, economics, political science, cultural studies, computer science, etc.

Improving social capital : a social network monitoring system. 'Mejorar el capital social : un sistema de red de control social'.

Resumen tomado del autor

SB.TV's successful yet unconventional establishment of a Brand based solely on Social Network Success may present a problem in long-term survival

Research Proposal in SB.TV case study. New dimension to brand model for Web 2.0 success