Showing papers on "Social network published in 2011"

Friendship and mobility: user movement in location-based social networks

Abstract: Even though human movement and mobility patterns have a high degree of freedom and variation, they also exhibit structural patterns due to geographic and social constraints. Using cell phone location data, as well as data from two online location-based social networks, we aim to understand what basic laws govern human motion and dynamics. We find that humans experience a combination of periodic movement that is geographically limited and seemingly random jumps correlated with their social networks. Short-ranged travel is periodic both spatially and temporally and not effected by the social network structure, while long-distance travel is more influenced by social network ties. We show that social relationships can explain about 10% to 30% of all human movement, while periodic behavior explains 50% to 70%. Based on our findings, we develop a model of human mobility that combines periodic short range movements with travel due to the social network structure. We show that our model reliably predicts the locations and dynamics of future human movement and gives an order of magnitude better performance than present models of human mobility.

Clinical Report—The Impact of Social Media on Children, Adolescents, and Families

Abstract: social media Web sites is among the most common activity of today's children and adolescents. Any Web site that allows social inter- action is considered a social media site, including social networking sites such as Facebook, MySpace, and Twitter; gaming sites and virtual worlds such as Club Penguin, Second Life, and the Sims; video sites such as YouTube; and blogs. Such sites offer today's youth a portal for entertainment and communication and have grown exponentially in recent years. For this reason, it is important that parents become aware of the nature of social media sites, given that not all of them are healthy environments for children and adolescents. Pediatricians are in a unique position to help families understand these sites and to encourage healthy use and urge parents to monitor for potential prob- lems with cyberbullying, "Facebook depression," sexting, and exposure to inappropriate content. Pediatrics 2011;127:800-804 SOCIAL MEDIA USE BY TWEENS AND TEENS Engaging in various forms of social media is a routine activity that research has shown to benefit children and adolescents by enhancing communication, social connection, and even technical skills. 1 Social media sites such as Facebook and MySpace offer multiple daily oppor- tunities for connecting with friends, classmates, and people with shared interests. During the last 5 years, the number of preadoles- cents and adolescents using such sites has increased dramatically. According to a recent poll, 22% of teenagers log on to their favorite social media site more than 10 times a day, and more than half of adolescents log on to a social media site more than once a day. 2 Seventy-five percent of teenagers now own cell phones, and 25% use them for social media, 54% use them for texting, and 24% use them for instant messaging. 3 Thus, a large part of this generation's social and

Connection Strategies: Social Capital Implications of Facebook-enabled Communication Practices

Abstract: This study assesses whether Facebook users have different ‘connection strategies,’ a term which describes a suite of Facebook-related relational communication activities, and explores the relationship between these connection strategies and social capital. Survey data (N = 450) from a random sample of undergraduate students reveal that only social information-seeking behaviors contribute to perceptions of social capital; connection strategies that focus on strangers or close friends do not. We also find that reporting more ‘actual’ friends on the site is predictive of social capital, but only to a point. We believe the explanation for these findings may be that the identity information in Facebook serves as a social lubricant, encouraging individuals to convert latent to weak ties and enabling them to broadcast requests for support or information.

On Network Theory

Abstract: Research on social networks has grown considerably in the last decade. However, there is a certain amount of confusion about network theory — for example, what it is, what is distinctive about it, and how to generate new theory. This paper attempts to remedy the situation by clarifying the fundamental concepts of the field (such as the network) and characterizing how network reasoning works. We start by considering the definition of network, noting some confusion caused by two different perspectives, which we refer to as realist and nominalist. We then analyze two well-known network theories, Granovetter’s strength of weak ties, to identify characteristic elements of network theorizing. We argue that both theories share an underlying theoretical model, which we label the network flow model, from which we derive additional implications. We also discuss network phenomena that do not appear to fit the flow model and discuss the possibility of a second fundamental model, which we call the bond model. We close with a discussion of the merits of model-based network theorizing for facilitating the generation of new theory, as well as a discussion of endogeneity in network theorizing.

On Network Theory

Abstract: Research on social networks has grown considerably in the last decade. However, there is a certain amount of confusion about network theory---for example, what it is, what is distinctive about it, and how to generate new theory. This paper attempts to remedy the situation by clarifying the fundamental concepts of the field (such as the network) and characterizing how network reasoning works. We start by considering the definition of network, noting some confusion caused by two different perspectives, which we refer to as realist and nominalist. We then analyze two well-known network theories, Granovetter's strength of weak ties theory [Granovetter, M. S. 1973. The strength of weak ties. Amer. J. Sociol.78(6) 1360--1380] and Burt's structural holes theory [Burt, R. S. 1992. Structural Holes: The Social Structure of Competition. Havard University Press, Cambridge, MA], to identify characteristic elements of network theorizing. We argue that both theories share an underlying theoretical model, which we label the network flow model, from which we derive additional implications. We also discuss network phenomena that do not appear to fit the flow model and discuss the possibility of a second fundamental model, which we call the bond model. We close with a discussion of the merits of model-based network theorizing for facilitating the generation of new theory, as well as a discussion of endogeneity in network theorizing.

The Anatomy of the Facebook Social Graph

Abstract: We study the structure of the social graph of active Facebook users, the largest social network ever analyzed. We compute numerous features of the graph including the number of users and friendships, the degree distribution, path lengths, clustering, and mixing patterns. Our results center around three main observations. First, we characterize the global structure of the graph, determining that the social network is nearly fully connected, with 99.91% of individuals belonging to a single large connected component, and we confirm the "six degrees of separation" phenomenon on a global scale. Second, by studying the average local clustering coefficient and degeneracy of graph neighborhoods, we show that while the Facebook graph as a whole is clearly sparse, the graph neighborhoods of users contain surprisingly dense structure. Third, we characterize the assortativity patterns present in the graph by studying the basic demographic and network properties of users. We observe clear degree assortativity and characterize the extent to which "your friends have more friends than you". Furthermore, we observe a strong effect of age on friendship preferences as well as a globally modular community structure driven by nationality, but we do not find any strong gender homophily. We compare our results with those from smaller social networks and find mostly, but not entirely, agreement on common structural network characteristics.

Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter

Abstract: Individual happiness is a fundamental societal metric. Normally measured through self-report, happiness has often been indirectly characterized and overshadowed by more readily quantifiable economic indicators such as gross domestic product. Here, we examine expressions made on the online, global microblog and social networking service Twitter, uncovering and explaining temporal variations in happiness and information levels over timescales ranging from hours to years. Our data set comprises over 46 billion words contained in nearly 4.6 billion expressions posted over a 33 month span by over 63 million unique users. In measuring happiness, we construct a tunable, real-time, remote-sensing, and non-invasive, text-based hedonometer. In building our metric, made available with this paper, we conducted a survey to obtain happiness evaluations of over 10,000 individual words, representing a tenfold size improvement over similar existing word sets. Rather than being ad hoc, our word list is chosen solely by frequency of usage, and we show how a highly robust and tunable metric can be constructed and defended.

Homophily and Contagion Are Generically Confounded in Observational Social Network Studies.

Abstract: The authors consider processes on social networks that can potentially involve three factors: homophily, or the formation of social ties due to matching individual traits; social contagion, also known as social influence; and the causal effect of an individual’s covariates on his or her behavior or other measurable responses. The authors show that generically, all of these are confounded with each other. Distinguishing them from one another requires strong assumptions on the parametrization of the social process or on the adequacy of the covariates used (or both). In particular the authors demonstrate, with simple examples, that asymmetries in regression coefficients cannot identify causal effects and that very simple models of imitation (a form of social contagion) can produce substantial correlations between an individual’s enduring traits and his or her choices, even when there is no intrinsic affinity between them. The authors also suggest some possible constructive responses to these results.

Human mobility, social ties, and link prediction

Abstract: Our understanding of how individual mobility patterns shape and impact the social network is limited, but is essential for a deeper understanding of network dynamics and evolution. This question is largely unexplored, partly due to the difficulty in obtaining large-scale society-wide data that simultaneously capture the dynamical information on individual movements and social interactions. Here we address this challenge for the first time by tracking the trajectories and communication records of 6 Million mobile phone users. We find that the similarity between two individuals' movements strongly correlates with their proximity in the social network. We further investigate how the predictive power hidden in such correlations can be exploited to address a challenging problem: which new links will develop in a social network. We show that mobility measures alone yield surprising predictive power, comparable to traditional network-based measures. Furthermore, the prediction accuracy can be significantly improved by learning a supervised classifier based on combined mobility and network measures. We believe our findings on the interplay of mobility patterns and social ties offer new perspectives on not only link prediction but also network dynamics.

Online Social Networking by Patients with Diabetes: A Qualitative Evaluation of Communication with Facebook

Abstract: Background Several disease-specific information exchanges now exist on Facebook and other online social networking sites. These new sources of knowledge, support, and engagement have become important for patients living with chronic disease, yet the quality and content of the information provided in these digital arenas are poorly understood.

Bayesian Learning in Social Networks

Abstract: We study the (perfect Bayesian) equilibrium of a sequential learning model over a general social network. Each individual receives a signal about the underlying state of the world, observes the past actions of a stochastically generated neighbourhood of individuals, and chooses one of two possible actions. The stochastic process generating the neighbourhoods defines the network topology. We characterize pure strategy equilibria for arbitrary stochastic and deterministic social networks and characterize the conditions under which there will be asymptotic learning—convergence (in probability) to the right action as the social network becomes large. We show that when private beliefs are unbounded (meaning that the implied likelihood ratios are unbounded), there will be asymptotic learning as long as there is some minimal amount of “expansion in observations”. We also characterize conditions under which there will be asymptotic learning when private beliefs are bounded.

Social capital on facebook: differentiating uses and users

Abstract: Though social network site use is often treated as a monolithic activity, in which all time is equally social and its impact the same for all users, we examine how Facebook affects social capital depending upon: (1) types of site activities, contrasting one-on-one communication, broadcasts to wider audiences, and passive consumption of social news, and (2) individual differences among users, including social communication skill and self-esteem. Longitudinal surveys matched to server logs from 415 Facebook users reveal that receiving messages from friends is associated with increases in bridging social capital, but that other uses are not. However, using the site to passively consume news assists those with lower social fluency draw value from their connections. The results inform site designers seeking to increase social connectedness and the value of those connections.

The dynamics of protest recruitment through an online network.

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

Predicting popular messages in Twitter

Abstract: Social network services have become a viable source of information for users. In Twitter, information deemed important by the community propagates through retweets. Studying the characteristics of such popular messages is important for a number of tasks, such as breaking news detection, personalized message recommendation, viral marketing and others. This paper investigates the problem of predicting the popularity of messages as measured by the number of future retweets and sheds some light on what kinds of factors influence information propagation in Twitter. We formulate the task into a classification problem and study two of its variants by investigating a wide spectrum of features based on the content of the messages, temporal information, metadata of messages and users, as well as structural properties of the users' social graph on a large scale dataset. We show that our method can successfully predict messages which will attract thousands of retweets with good performance.

Social Network Analysis: History, Theory and Methodology

Abstract: We live in a world that is paradoxically small and vast: each of us is embedded in local communities and yet we are only a few 'links' away from anyone else in the world. This engaging book represents these interdependencies' positive and negative consequences, their multiple effects and the ways in which a local occurrence in one part of the world can directly affect the rest. Then it demonstrates precisely how these interactions and relationships form. This is a book for the social network novice on learning how to study, think about and analyse social networks; the intermediate user, not yet familiar with some of the newer developments in the field; and the teacher looking for a range of exercises, as well as an up-to-date historical account of the field. It is divided into three sections: 1. Historical & Background Concepts 2. Levels of Analysis 3. Advances, Extensions and Conclusions The book provides a full overview of the field - historical origins, common theoretical perspectives and frameworks; traditional and current analytical procedures and fundamental mathematical equations needed to get a foothold in the field.

Network Effects and Personal Influences: The Diffusion of an Online Social Network:

Abstract: This article discusses the diffusion process in an online social network given the individual connections between members. The authors model the adoption decision of individuals as a binary choice affected by three factors: (1) the local network structure formed by already adopted neighbors, (2) the average characteristics of adopted neighbors (influencers), and (3) the characteristics of the potential adopters. Focusing on the first factor, the authors find two marked effects. First, an individual who is connected to many adopters has a greater adoption probability (degree effect). Second, the density of connections in a group of already adopted consumers has a strong positive effect on the adoption of individuals connected to this group (clustering effect). The article also records significant effects for influencer and adopter characteristics. For adopters, specifically, the authors find that position in the entire network and some demographic variables are good predictors of adoption. Similar...

Understanding Social Networks: Theories, Concepts, and Findings

Abstract: Preface 1) Introduction -Getting Connected -Networks as Information Maps -Leaders and Followers -Networks as Conduits -The Point of View 2) Basic Network Concepts, Part I: Individual Members of Networks -Introduction -What Is a Network? -Sociological Questions about Relationships Connections Propinquity Homophily Individual-Level Homophily Homophily and Collectivities -Dyads and Mutuality -Balance and Triads -Where We Are Now 3) Basic Network Concepts, Part II: Whole Social Networks -Distributions Dyads and Triads Density Structural Holes Weak Ties -"Popularity" or Centrality -Distance Size of the Interpersonal Environment The "Small World" -Multiplexity -Roles and Positions Named Positions and Relationships Informal Positions and Relationships Informal Relations and Hierarchies Embeddedness of the Informal within Instituted or Named Networks Observed Roles -Summary 4) Basic Network Concepts, Part III: Network Segmentation -Introduction -Named and Unnamed Network Segments Primary Groups, Cliques, and Clusters -Segmenting Networks from the Point of View of the Observer Segmenting Groups on the Basis of Cohesion Resistance to Disruption Structural Similarity and Structural Equivalence Core/Periphery Structures -Where We Are Now 5) The Psychological Foundations of Social Networks -Getting Things Done -Community and Support -Safety and Affiliation -Effectiveness and Structural Holes -Safety and Social Networks -Effectiveness and Social Networks -Both Safety and Effectiveness? -Driving for Status or Rank -Cultural Differences in Safety, Effectance, and Rank -Motivations and Practical Networks -Motivations of Corporate Actors -Cognitive Limits on Individual Networks -Where We Are Now 6) Small Groups, Leadership, and Social Networks: The Basic Building Blocks -Introduction -Primary Groups and Informal Systems: Propositions -Pure Informal Systems -How to Find Informal Systems -Asymmetric Ties and the Influence of the External System -Formalizing the System -Where We Are Now 7) Organizations and Networks -The Contradictions of Authority -Emergent Networks in Organizations The Factory Floor -Information-Driven Organizations -Inside the Box, Outside the Box, or Both -Bridging the Gaps: Tradeoff s between Network Size, Diversity, and Social Cohesion -Where We Are Now 8) The Small World, Circles, and Communities -Introduction -How Many People Do You Know? -The Skewed Distribution of the Number of People One Knows -Formal Small World Models -Clustering in Social Networks -Social Circles -The Small World Search -Applications of Small World Theory to Smaller Worlds -Where We Are Now 9) Networks and Diffusion -Networks and Diffusion-An Introduction The Basic Model Exogenous Factors in the Adoption of Innovation - Influence and Decision-Making The Current State of Personal Influence Self-Designated Opinion Leaders or Influentials Characteristics of Opinion Leaders and Influentials Group Influence -Epidemiology and Network Diffusion Social Networks and Epidemiology Social Networks and HIV-AIDS Transporting Disease-Large-Scale Models -Tipping Points and Thresholds Threshold - Where We Are Now 10) Networks as Social Capital - Introduction The General Idea of Social Capital Social Capital as Investment -Individual-Level Social Capital Social Support Individual Networked Resources: Position and Resource Generators Correlates of Individual Social Capital Other Indicators of Networked Resources -Social Capital as an Attribute of Social Systems Theorists of Social System Social Capital Bowling Alone Recent Findings on Social System Social Capital and Its Consequences -Where We Are Now 11) Ethical Dilemmas of Network Research -Networks as a Research Paradigm -Anonymity, Confidentiality, Privacy, and Consent -Who Benefits - Cases and Examples Survey Research Organization Research Terrorists and Criminals Networks and Terrorism: The CASOS Projects -Conclusion: More Complicated than the Belmont Report 12) Coda: Ten Master Ideas of Social Networks -Introduction -The Ten Master Ideas Bibliography Notes Index

Radicalization into Violent Extremism I: A Review of Social Science Theories

Abstract: In discourse about countering terrorism, the term "radicalization" is widely used, but remains poorly defined To focus narrowly on ideological radicalization risks implying that radical beliefs are a proxy—or at least a necessary precursor—for terrorism, though we know this not to be trueDifferent pathways and mechanisms of terrorism involvement operate in different ways for different people at different points in time and perhaps in different contexts This article explores the problems in defining radicalization and radicalism, and suggests that radicalization—and more specifically, involvement in terrorism—might best be viewed as a set of diverse processes It goes on to review several potentially promising theories that might support further study of those processes, including social movement theory, social psychology, and conversion theory Finally, it describes some possible frameworks for understanding how the processes might facilitate terrorism-related behavior This article is available in Journal of Strategic Security: http://scholarcommonsusfedu/jss/vol4/iss4/2 Journal of Strategic Security Volume 4 Issue 4 2011, pp 7-36 DOI: 105038/1944-0472441 Journal of Strategic Security (c) 2011 ISSN: 1944-0464 eISSN: 1944-0472 7 Radicalization into Violent Extremism I: A Review of Social Science Theories Randy Borum University of South Florida wborum@usfedu

Analyzing facebook privacy settings: user expectations vs. reality

Abstract: The sharing of personal data has emerged as a popular activity over online social networking sites like Facebook. As a result, the issue of online social network privacy has received significant attention in both the research literature and the mainstream media. Our overarching goal is to improve defaults and provide better tools for managing privacy, but we are limited by the fact that the full extent of the privacy problem remains unknown; there is little quantification of the incidence of incorrect privacy settings or the difficulty users face when managing their privacy.In this paper, we focus on measuring the disparity between the desired and actual privacy settings, quantifying the magnitude of the problem of managing privacy. We deploy a survey, implemented as a Facebook application, to 200 Facebook users recruited via Amazon Mechanical Turk. We find that 36% of content remains shared with the default privacy settings. We also find that, overall, privacy settings match users' expectations only 37% of the time, and when incorrect, almost always expose content to more users than expected. Finally, we explore how our results have potential to assist users in selecting appropriate privacy settings by examining the user-created friend lists. We find that these have significant correlation with the social network, suggesting that information from the social network may be helpful in implementing new tools for managing privacy.

Exploiting place features in link prediction on location-based social networks

Abstract: Link prediction systems have been largely adopted to recommend new friends in online social networks using data about social interactions. With the soaring adoption of location-based social services it becomes possible to take advantage of an additional source of information: the places people visit. In this paper we study the problem of designing a link prediction system for online location-based social networks. We have gathered extensive data about one of these services, Gowalla, with periodic snapshots to capture its temporal evolution. We study the link prediction space, finding that about 30% of new links are added among "place-friends", i.e., among users who visit the same places. We show how this prediction space can be made 15 times smaller, while still 66% of future connections can be discovered. Thus, we define new prediction features based on the properties of the places visited by users which are able to discriminate potential future links among them.Building on these findings, we describe a supervised learning framework which exploits these prediction features to predict new links among friends-of-friends and place-friends. Our evaluation shows how the inclusion of information about places and related user activity offers high link prediction performance. These results open new directions for real-world link recommendation systems on location-based social networks.

SIoT: Giving a Social Structure to the Internet of Things

Abstract: The actual development of the Internet of Things (IoT) needs major issues related to things' service discovery and composition to be addressed. This paper proposes a possible approach to solve such issues. We introduce a novel paradigm of "social network of intelligent objects", namely the Social Internet of Things (SIoT), based on the notion of social relationships among objects. Following the definition of a possible social structure among objects, a preliminary architecture for the implementation of SIoT is presented. Through the SIoT paradigm, the capability of humans and devices to discover, select, and use objects with their services in the IoT is augmented. Besides, a level of trustworthiness is enabled to steer the interaction among the billions of objects which will crowd the future IoT.

Comparing Community Structure to Characteristics in Online Collegiate Social Networks

Abstract: We study the structure of social networks of students by examining the graphs of Facebook “friendships” at five U.S. universities at a single point in time. We investigate the community structure of each single-institution network and employ visual and quantitative tools, including standardized pair-counting methods, to measure the correlations between the network communities and a set of self-identified user characteristics (residence, class year, major, and high school). We review the basic properties and statistics of the employed pair-counting indices and recall, in simplified notation, a useful formula for the $z$-score of the Rand coefficient. Our study illustrates how to examine different instances of social networks constructed in similar environments, emphasizes the array of social forces that combine to form “communities,” and leads to comparative observations about online social structures, which reflect offline social structures. We calculate the relative contributions of different characteristics to the community structure of individual universities and compare these relative contributions at different universities. For example, we examine the importance of common high school affiliation at large state universities and the varying degrees of influence that common major can have on the social structure at different universities. The heterogeneity of the communities that we observe indicates that university networks typically have multiple organizing factors rather than a single dominant one.

A networked self : identity, community, and culture on social network sites

Abstract: Introduction and Keynote to the Networked Self Albert-Laszlo Barabasi Part One Context: Communication Theory and Social Network Sites 1. Interaction of Interpersonal, Peer, and Media Influence Sources Online: A Research Agenda for Technology Convergence Joseph B. Walther, Caleb Carr, Scott Seung W. Choi, David DeAndrea, Jinsuk Kim, Stephanie Tom Tong, Brandon Van Der Heide 2. Social Network Sites as Networked Publics: Affordances, Dynamics, and Implication danah boyd 3. Addictive, Compulsive, or Just Another Habit? Robert LaRose, Junghyun Kim, and Wei Peng 4. Social Network Exploitation Mark Andrejevic Part Two Social Textures: Emerging Patterns of Sociability on Social Network Sites 5. Social Network Sites as Virtual Communities Malcolm R. Parks 6. "With a little help from my Friends: How social network sites affect social capital processes" Nicole Ellison, Cliff Lampe, Charles Steinfield, and Jessica Vitak 7. From Dabblers to Omnivores:A Typology of Social Network Site Usage Eszter Hargittai and Yu-Li Patrick Hsieh 8. Exploring the Use of Social Network Sites in the Workplace Mary Beth Watson-Manheim Part Three Convergent Practices:Intuitive Appropriations of SNS Affordances 9. United We Stand? Online Social Nework Sites and Civic Engagement Thomas J. Johnson, Weiwu Zhang, Shannon L. Bichard, and Trent Seltzer 10. Between Barack and a Net Place: Users and Uses of Social Network Sites and Blogs for Political Information Barbara K. Kaye 11. Working the Twittersphere: Microblogging as professional identity construction Dawn Gilpin 12. Look at us: Collective Narcissism in College Student Facebook Photo Galleries Andrew L. Mendelson and Zizi Papacharissi 13. Copyright, Fair Use and Social Networks Patricia Aufderheide 14. Artificial Agents Entering Social Networks Nikolaos Mavridis Conclusion: A Networked Self Zizi Papacharissi