Showing papers on "Social network published in 2015"

Maximizing the Spread of Influence through a Social Network

Abstract: Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technological innovations, the sudden and widespread adoption of various strategies in game-theoretic settings, and the effects of "word of mouth" in the promotion of new products. Recently, motivated by the design of viral marketing strategies, Domingos and Richardson posed a fundamental algorithmic problem for such social network processes: if we can try to convince a subset of individuals to adopt a new product or innovation, and the goal is to trigger a large cascade of further adoptions, which set of individuals should we target?We consider this problem in several of the most widely studied models in social network analysis. The optimization problem of selecting the most influential nodes is NP-hard here, and we provide the first provable approximation guarantees for efficient algorithms. Using an analysis framework based on submodular functions, we show that a natural greedy strategy obtains a solution that is provably within 63% of optimal for several classes of models; our framework suggests a general approach for reasoning about the performance guarantees of algorithms for these types of influence problems in social networks.We also provide computational experiments on large collaboration networks, showing that in addition to their provable guarantees, our approximation algorithms significantly out-perform node-selection heuristics based on the well-studied notions of degree centrality and distance centrality from the field of social networks.

Consumer engagement in online brand communities: a social media perspective

Abstract: Purpose – This paper aims to delineate the meaning, conceptual boundaries and dimensions of consumer engagement within the context of online brand communities both in term of the engagement with the brand and the other members of the online brand communities. It also explores the relationships of consumer engagement with other concepts, suggesting antecedents of engagement. Design/methodology/approach – Data are collected through semi-structured interviews with 21 international online brand community members, covering a variety of brand categories and social media platforms. Findings – This paper suggests that individuals are engaging in online communities in social network platforms both with other individuals and with brands. The study also identifies three key engagement dimensions (cognition, affect and behaviours). Their meaning and sub-dimensions are investigated. The paper further suggests key drivers, one outcome and objects of consumer engagement in online brand communities. These findings are in...

The Platformization of the Web: Making Web Data Platform Ready

Abstract: In this article, I inquire into Facebook’s development as a platform by situating it within the transformation of social network sites into social media platforms. I explore this shift with a histo...

Using Social Network Sites: The Effects of Playfulness, Critical Mass and Trust in a Hedonic Context

Abstract: The use of Internet social network sites has become an international phenomenon. These websites enable computer-mediated communication between people with common interests such as school, family, and friendship. Popular sites include MySpace and Facebook. Their rapid widespread usage warrants a better understanding. This study contributes to our understanding by empirically investigating factors influencing user adoption of these sites. We introduce the Social Network Site Adoption model to examine the effect of perceptions of normative pressure, playfulness, critical mass, trust, usefulness, and ease of use on usage intention and actual usage of these sites. Structural equation modeling was used to examine the patterns of inter-correlations among the constructs and to empirically test the hypotheses. All the hypothesized determinants have a significant direct effect on intent to use, with perceived playfulness and perceived critical mass the strongest indicators. Intent to use and perceived playfulness h...

Experimentally induced innovations lead to persistent culture via conformity in wild birds

Abstract: In human societies, cultural norms arise when behaviours are transmitted through social networks via high-fidelity social learning. However, a paucity of experimental studies has meant that there is no comparable understanding of the process by which socially transmitted behaviours might spread and persist in animal populations. Here we show experimental evidence of the establishment of foraging traditions in a wild bird population. We introduced alternative novel foraging techniques into replicated wild sub-populations of great tits (Parus major) and used automated tracking to map the diffusion, establishment and long-term persistence of the seeded innovations. Furthermore, we used social network analysis to examine the social factors that influenced diffusion dynamics. From only two trained birds in each sub-population, the information spread rapidly through social network ties, to reach an average of 75% of individuals, with a total of 414 knowledgeable individuals performing 57,909 solutions over all replicates. The sub-populations were heavily biased towards using the technique that was originally introduced, resulting in established local traditions that were stable over two generations, despite a high population turnover. Finally, we demonstrate a strong effect of social conformity, with individuals disproportionately adopting the most frequent local variant when first acquiring an innovation, and continuing to favour social information over personal information. Cultural conformity is thought to be a key factor in the evolution of complex culture in humans. In providing the first experimental demonstration of conformity in a wild non-primate, and of cultural norms in foraging techniques in any wild animal, our results suggest a much broader taxonomic occurrence of such an apparently complex cultural behaviour.

Social Media Definition and the Governance Challenge: An Introduction to the Special Issue

Abstract: This introduction to a special issue of "Telecommunications Policy" entitled "The Governance of Social Media" begins with a definition of social media that informs all contributions in the special issue. A section describing the challenges associated with the governance of social media is presented next, followed by an overview of the various articles included in the special issue.While the Internet and the World Wide Web have always been used to facilitate social interaction, the emergence and rapid diffusion of Web 2.0 functionalities during the first decade of the new millennium enabled an evolutionary leap forward in the social component of web use. This and falling costs for online data storage made it feasible for the first time to offer masses of Internet users access to an array of user-centric spaces they could populate with user-generated content, along with a correspondingly diverse set of opportunities for linking these spaces together to form virtual social networks.To define “social media” for our current purposes, we synthesize definitions presented in the literature and identify the following commonalities among current social media services:1) Social media services are (currently) Web 2.0 Internet-based applications,2) User-generated content is the lifeblood of social media,3) Individuals and groups create user-specific profiles for a site or app designed and maintained by a social media service,4) Social media services facilitate the development of social networks online by connecting a profile with those of other individuals and/or groups.Transformative communication technologies have always called for regulatory innovation. Theodor Vail’s vision of “one policy, one system, universal service” preceded more than one-hundred years of innovative regulations aimed at connecting all Americans to a single telephone network. The sinking of the Titanic, caused in part by “chaos in the spectrum” led to the Radio Act of 1912 and the creation of a command and control model designed to regulate broadcast radio. Safe-harbor hours were put in place after a father and son heard George Carlin’s “seven dirty words” routine over the radio in their car. The fairness doctrine and the minority tax certificate program were designed to address inequalities in the broadcast television industry. The Digital Millennium Copyright Act responded to intellectual property concerns raised by a global Internet and the FCC’s 700mhz auction was the result of demand for smarter mobile phones. Now we must consider the role of regulatory innovation in response to the emergence of social media.

Social Media: Defining, Developing, and Divining

Abstract: What is a social medium, and how may one moderate, isolate, and influence communicative processes within? Although scholars assume an inherent understanding of social media based on extant technology, there is no commonly accepted definition of what social media are, both functionally and theoretically, within communication studies. Given this lack of understanding, cogent theorizing regarding the uses and effects of social media has been limited. This work first draws on extant definitions of social media and subcategories (e.g., social network sites) from public relations, information technology, and management scholarship, as well as the popular press, to develop a definition of social media precise enough to embody these technologies yet robust enough to remain applicable in 2035. It then broadly explores emerging developments in the features, uses, and users of social media for which future theories will need to account. Finally, it divines and prioritizes challenges that may not yet be apparent to t...

Social Network Data Analytics

Abstract: 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 Properties of Social Networks, Algorithms for Structural Discovery of Social Networks and Content Analysis in Social Networks. This book is also unique in focussing on the data analytical aspects of social networks in the internet scenario, rather than the traditional sociology-driven emphasis prevalent in the existing books, which do not focus on the unique data-intensive characteristics of online social networks. Emphasis is placed on simplifying the content so that students and practitioners benefit from this book. This book targets advanced level students and researchers concentrating on computer science as a secondary text or reference book. Data mining, database, information security, electronic commerce and machine learning professionals will find this book a valuable asset, as well as primary associations such as ACM, IEEE and Management Science.

Link prediction in social networks: the state-of-the-art

Abstract: In social networks, link prediction predicts missing links in current networks and new or dissolution links in future networks, is important for mining and analyzing the evolution of social networks. In the past decade, many works have been done about the link prediction in social networks. The goal of this paper is to comprehensively review, analyze and discuss the state-of-the-art of the link prediction in social networks. A systematical category for link prediction techniques and problems is presented. Then link prediction techniques and problems are analyzed and discussed. Typical applications of link prediction are also addressed. Achievements and roadmaps of some active research groups are introduced. Finally, some future challenges of the link prediction in social networks are discussed.

Inferring social status and rich club effects in enterprise communication networks.

Abstract: Social status, defined as the relative rank or position that an individual holds in a social hierarchy, is known to be among the most important motivating forces in social behaviors. In this paper, we consider the notion of status from the perspective of a position or title held by a person in an enterprise. We study the intersection of social status and social networks in an enterprise. We study whether enterprise communication logs can help reveal how social interactions and individual status manifest themselves in social networks. To that end, we use two enterprise datasets with three communication channels — voice call, short message, and email — to demonstrate the social-behavioral differences among individuals with different status. We have several interesting findings and based on these findings we also develop a model to predict social status. On the individual level, high-status individuals are more likely to be spanned as structural holes by linking to people in parts of the enterprise networks that are otherwise not well connected to one another. On the community level, the principle of homophily, social balance and clique theory generally indicate a “rich club” maintained by high-status individuals, in the sense that this community is much more connected, balanced and dense. Our model can predict social status of individuals with 93% accuracy.

Social Networks and Health.

Abstract: 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.

Network analysis reveals open forums and echo chambers in social media discussions of climate change

Abstract: Action to tackle the complex and divisive issue of climate change will be strongly influenced by public perception. Online social media and associated social networks are an increasingly important forum for public debate and are known to influence individual attitudes and behaviours – yet online discussions and social networks related to climate change are not well understood. Here we construct several forms of social network for users communicating about climate change on the popular microblogging platform Twitter. We classify user attitudes to climate change based on message content and find that social networks are characterised by strong attitude-based homophily and segregation into polarised “sceptic” and “activist” groups. Most users interact only with like-minded others, in communities dominated by a single view. However, we also find mixed-attitude communities in which sceptics and activists frequently interact. Messages between like-minded users typically carry positive sentiment, while messages between sceptics and activists carry negative sentiment. We identify a number of general patterns in user behaviours relating to engagement with alternative views. Users who express negative sentiment are themselves the target of negativity. Users in mixed-attitude communities are less likely to hold a strongly polarised view, but more likely to express negative sentiment towards other users with differing views. Overall, social media discussions of climate change often occur within polarising “echo chambers”, but also within “open forums”, mixed-attitude communities that reduce polarisation and stimulate debate. Our results have implications for public engagement with this important global challenge.

Searching for superspreaders of information in real-world social media

Abstract: A number of predictors have been suggested to detect the most influential spreaders of information in online social media across various domains such as Twitter or Facebook. In particular, degree, PageRank, k-core and other centralities have been adopted to rank the spreading capability of users in information dissemination media. So far, validation of the proposed predictors has been done by simulating the spreading dynamics rather than following real information flow in social networks. Consequently, only model-dependent contradictory results have been achieved so far for the best predictor. Here, we address this issue directly. We search for influential spreaders by following the real spreading dynamics in a wide range of networks. We find that the widely-used degree and PageRank fail in ranking users' influence. We find that the best spreaders are consistently located in the k-core across dissimilar social platforms such as Twitter, Facebook, Livejournal and scientific publishing in the American Physical Society. Furthermore, when the complete global network structure is unavailable, we find that the sum of the nearest neighbors' degree is a reliable local proxy for user's influence. Our analysis provides practical instructions for optimal design of strategies for “viral” information dissemination in relevant applications.

Toward Social Internet of Vehicles: Concept, Architecture, and Applications

Abstract: The main vision of the Internet of Things (IoT) is to equip real-life physical objects with computing and communication power so that they can interact with each other for the social good. As one of the key members of IoT, Internet of Vehicles (IoV) has seen steep advancement in communication technologies. Now, vehicles can easily exchange safety, efficiency, infotainment, and comfort-related information with other vehicles and infrastructures using vehicular ad hoc networks (VANETs). We leverage on the cloud-based VANETs theme to propose cyber-physical architecture for the Social IoV (SIoV). SIoV is a vehicular instance of the Social IoT (SIoT), where vehicles are the key social entities in the machine-to-machine vehicular social networks. We have identified the social structures of SIoV components, their relationships, and the interaction types. We have mapped VANETs components into IoT-A architecture reference model to offer better integration of SIoV with other IoT domains. We also present a communication message structure based on automotive ontologies, the SAE J2735 message set, and the advanced traveler information system events schema that corresponds to the social graph. Finally, we provide the implementation details and the experimental analysis to demonstrate the efficacy of the proposed system as well as include different application scenarios for various user groups.

The Use of Enterprise Social Network Sites for Knowledge Sharing in Distributed Organizations: The Role of Organizational Affordances

Abstract: Enterprise social network sites (ESNSs) are increasingly being introduced into large multinational organizations. In this article, we consider their potential for supporting knowledge-sharing pract...

Social Network and Tag Sources Based Augmenting Collaborative Recommender System

Abstract: Recommender systems, which provide users with recommendations of content suited to their needs, have received great attention in today’s online business world. However, most recommendation approaches exploit only a single source of input data and suffer from the data sparsity problem and the cold start problem. To improve recommendation accuracy in this situation, additional sources of information, such as friend relationship and user-generated tags, should be incorporated in recommendation systems. In this paper, we revise the user-based collaborative filtering (CF) technique, and propose two recommendation approaches fusing usergenerated tags and social relations in a novel way. In order to evaluate the performance of our approaches, we compare experimental results with two baseline methods: user-based CF and user-based CF with weighted friendship similarity using the real datasets (Last.fm and Movielens). Our experimental results show that our methods get higher accuracy. We also verify our methods in cold-start settings, and our methods achieve more precise recommendations than the compared approaches. key words: recommender system, collaborative filtering, social tagging, social network

Doing Social Network Research: Network-based Research Design for Social Scientists

Abstract: The difference with social networks research Fundamental network concepts and ideas Thinking about networks: Research questions and study design Social systems and data structures: relational ties and actor attributes Network observation and measurement The empirical context of network data collection Ethical issues for social networks research Network visualization: What it can and cannot do A review of social network analytic methods Drawing conclusions: Inference, generalization, causality and other weighty matters

Social Media: A Contextual Framework to Guide Research and Practice

Abstract: Social media are a broad collection of digital platforms that have radically changed the way people interact and communicate. However, we argue that social media are not simply a technology but actually represent a context that differs in important ways from traditional (e.g., face-to-face) and other digital (e.g., email) ways of interacting and communicating. As a result, social media is a relatively unexamined type of context that may affect the cognition, affect, and behavior of individuals within organizations. We propose a contextual framework that identifies the discrete and ambient stimuli that distinguish social media contexts from digital communication media (e.g., email) and physical (e.g., face-to-face) contexts. We then use this contextual framework to demonstrate how it changes more person-centered theories of organizational behavior (e.g., social exchange, social contagion, and social network theories). These theoretical insights are also used to identify a number of practical implications for individuals and organizations. This study’s major contribution is creating a theoretical understanding of social media features so that future research may proceed in a theory-based, rather than platform-based, manner. Overall, we intend for this article to stimulate and broadly shape the direction of research on this ubiquitous, but poorly understood, phenomenon.

Social Networks and the Decision to Insure

Abstract: *Using data from a randomized experiment in rural China, we study the influence of social networks on weather insurance adoption and the mechanisms through which they operate. To quantify network effects, the experiment provides intensive information sessions about the product to a random subset of farmers. For untreated farmers, the effect of having an additional treated friend on take-up is equivalent to granting a 13 percent reduction in the insurance premium. By varying the information available about peers’ decisions and randomizing default options, we show that the network effect is driven by the diffusion of insurance knowledge rather than purchase decisions. (JEL G22, O12, O16, P36, Q12, Q54, Z13) inancial decisions involve complexities that individuals frequently have difficulty understanding based on their own education, information, and experience. Social networks can help people make these complex decisions: people can learn about product benefits from their friends, be influenced by their friends’ choices, and/or learn from their friends’ experiences with the product. This paper uses a novel experimental design to obtain clean measurements of the role and functioning of social networks in the decision to purchase a weather insurance product, which is typically hard for farmers to understand and has had a particularly low spontaneous take-up in most countries. We designed a randomized experiment based on the introduction of a new weather insurance policy for rice farmers offered by the People’s Insurance Company of China (PICC), China’s largest insurance provider. Implemented jointly with PICC, the experiment involved 5,300 households across 185 villages of rural China. Our experimental design allows us to not only identify the causal effect of social networks on product adoption, but also test for the role of various channels through which social networks operate. Furthermore, using a household-level price randomization, we calculate the price equivalence of the social network effect on insurance take-up. Finally, taking advantage of the substantial variation in network

Do Your Online Friends Make You Pay? A Randomized Field Experiment on Peer Influence in Online Social Networks

Abstract: Demonstrating compelling causal evidence of the existence and strength of peer-to-peer influence has become the holy grail of modern research in online social networks. In these networks, it has been consistently demonstrated that user characteristics and behavior tend to cluster both in space and in time. There are multiple well-known rival mechanisms that compete to be the explanation for this observed clustering. These range from peer influence to homophily to other unobservable external stimuli. These multiple mechanisms lead to similar observational data, yet have vastly different policy implications. In this paper, we present a novel randomized experiment that tests the existence of causal peer influence in the general population-one that did not involve subject recruitment for experimentation-of a particular large-scale online social network. We utilize a unique social feature to exogenously induce adoption of a paid service among a group of randomly selected users, and in the process develop a clean exogenous randomization of treatment and control groups. A variety of nonparametric, semiparametric, and parametric approaches, ranging from resampling-based inference to ego-level random effects to logistic regression to survival models, yield close to identical, statistically and economically significant estimates of peer influence in the general population of a freemium social network. Our estimates show that peer influence causes more than a 60% increase in odds of buying the service due to the influence coming from an adopting friend. In addition, we find that users with a smaller number of friends experience stronger relative increase in the adoption likelihood due to influence from their peers as compared to the users with a larger number of friends. Our nonparametric resampling procedure-based estimates are helpful in situations of networked data that violate independence assumptions. We establish that peer influence is a powerful force in getting users from free to premium levels, a known challenge in freemium communities. This paper was accepted by Sandra Slaughter, information systems.

Integrating social communities and wagering games

Abstract: A wagering game system and its operations are described herein. In some examples, the operations include connecting social network user accounts to a communal wagering game. The operations can further include determining, via a network communication interface, an electronic request associated with a first social network user account to transact an electronic exchange, with a second social network user account, of one or more non-cash items associated with the communal wagering game. The operations can further include accessing, via an electronic processing unit, a first memory storage unit of the gaming system associated with the first social network user account. The first memory storage unit specifies the one or more non-cash items. The operations can further include transacting, via the network communication interface, the electronic exchange of the one or more non-cash items between the first social network user account and the second social network user account.

COSNET: Connecting Heterogeneous Social Networks with Local and Global Consistency

Abstract: More often than not, people are active in more than one social network. Identifying users from multiple heterogeneous social networks and integrating the different networks is a fundamental issue in many applications. The existing methods tackle this problem by estimating pairwise similarity between users in two networks. However, those methods suffer from potential inconsistency of matchings between multiple networks.In this paper, we propose COSNET (COnnecting heterogeneous Social NETworks with local and global consistency), a novel energy-based model, to address this problem by considering both local and global consistency among multiple networks. An efficient subgradient algorithm is developed to train the model by converting the original energy-based objective function into its dual form.We evaluate the proposed model on two different genres of data collections: SNS and Academia, each consisting of multiple heterogeneous social networks. Our experimental results validate the effectiveness and efficiency of the proposed model. On both data collections, the proposed COSNET method significantly outperforms several alternative methods by up to 10-30% (p

Topography of social touching depends on emotional bonds between humans

Abstract: Nonhuman primates use social touch for maintenance and reinforcement of social structures, yet the role of social touch in human bonding in different reproductive, affiliative, and kinship-based relationships remains unresolved. Here we reveal quantified, relationship-specific maps of bodily regions where social touch is allowed in a large cross-cultural dataset (N = 1,368 from Finland, France, Italy, Russia, and the United Kingdom). Participants were shown front and back silhouettes of human bodies with a word denoting one member of their social network. They were asked to color, on separate trials, the bodily regions where each individual in their social network would be allowed to touch them. Across all tested cultures, the total bodily area where touching was allowed was linearly dependent (mean r(2) = 0.54) on the emotional bond with the toucher, but independent of when that person was last encountered. Close acquaintances and family members were touched for more reasons than less familiar individuals. The bodily area others are allowed to touch thus represented, in a parametric fashion, the strength of the relationship-specific emotional bond. We propose that the spatial patterns of human social touch reflect an important mechanism supporting the maintenance of social bonds.

Exploiting social ties for cooperative D2D communications: a mobile social networking case

Abstract: Thanks to the convergence of pervasive mobile communications and fast-growing online social networking, mobile social networking is penetrating into our everyday life. Aiming to develop a systematic understanding of mobile social networks, in this paper we exploit social ties in human social networks to enhance cooperative device-to-device (D2D) communications. Specifically, as handheld devices are carried by human beings, we leverage two key social phenomena, namely social trust and social reciprocity, to promote efficient cooperation among devices. With this insight, we develop a coalitional game-theoretic framework to devise social-tie-based cooperation strategies for D2D communications. We also develop a network-assisted relay selection mechanism to implement the coalitional game solution, and show that the mechanism is immune to group deviations, individually rational, truthful, and computationally efficient. We evaluate the performance of the mechanism by using real social data traces. Simulation results corroborate that the proposed mechanism can achieve significant performance gain over the case without D2D cooperation.

A Survey on Vehicular Social Networks

Abstract: This paper surveys recent literature on vehicular social networks that are a particular class of vehicular ad hoc networks, characterized by social aspects and features. Starting from this pillar, we investigate perspectives on next-generation vehicles under the assumption of social networking for vehicular applications (i.e., safety and entertainment applications). This paper plays a role as a starting point about socially inspired vehicles and mainly related applications, as well as communication techniques. Vehicular communications can be considered the “first social network for automobiles” since each driver can share data with other neighbors. For instance, heavy traffic is a common occurrence in some areas on the roads (e.g., at intersections, taxi loading/unloading areas, and so on); as a consequence, roads become a popular social place for vehicles to connect to each other. Human factors are then involved in vehicular ad hoc networks, not only due to the safety-related applications but also for entertainment purposes. Social characteristics and human behavior largely impact on vehicular ad hoc networks, and this arises to the vehicular social networks, which are formed when vehicles (individuals) “socialize” and share common interests. In this paper, we provide a survey on main features of vehicular social networks, from novel emerging technologies to social aspects used for mobile applications, as well as main issues and challenges. Vehicular social networks are described as decentralized opportunistic communication networks formed among vehicles. They exploit mobility aspects, and basics of traditional social networks , in order to create novel approaches of message exchange through the detection of dynamic social structures. An overview of the main state-of-the-art on safety and entertainment applications relying on social networking solutions is also provided.

Agent-based modeling of energy technology adoption

Abstract: Agent-based modeling (ABM) techniques for studying human-technical systems face two important challenges. First, agent behavioral rules are often ad hoc, making it difficult to assess the implications of these models within the larger theoretical context. Second, the lack of relevant empirical data precludes many models from being appropriately initialized and validated, limiting the value of such models for exploring emergent properties or for policy evaluation. To address these issues, in this paper we present a theoretically-based and empirically-driven agent-based model of technology adoption, with an application to residential solar photovoltaic (PV). Using household-level resolution for demographic, attitudinal, social network, and environmental variables, the integrated ABM framework we develop is applied to real-world data covering 2004-2013 for a residential solar PV program at the city scale. Two applications of the model focusing on rebate program design are also presented. We develop an integrated agent-based model of residential solar adoption.Model is based upon a theoretically-driven behavioral model and data collection.Multiple data-streams are merged to enable empirical initialization of agent states.We use a technology-specific social network, leveraging observed geographic patterns.Model is validated using multiple (temporal, spatial, and demographic) criteria.

Measuring the Degree of Corporate Social Media Use.

Abstract: This article aims to provide a model with which to measure the degree of corporate social media use or, in other words, the extent to which companies are exploiting the potentialities of single or ...

Social Network Assessments and Interventions for Health Behavior Change: A Critical Review

Abstract: Social networks provide a powerful approach for health behavior change. This article documents how social network interventions have been successfully used for a range of health behaviors, including HIV risk practices, smoking, exercise, dieting, family planning, bullying, and mental health. We review the literature that suggests the relationship between health behaviors and social network attributes demonstrates a high degree of specificity. The article then examines hypothesized social influence mechanisms including social norms, modeling, and social rewards and the factors of social identity and social rewards that can be employed to sustain social network interventions. Areas of future research avenues are highlighted, including the need to examine and to adjust analytically for contamination and social diffusion, social influence versus differential affiliation, and network change. Use and integration of mhealth and face-to-face networks for promoting health behavior change are also critical research areas.