Models,methods and network topology: Experimental design for the study of interference

How should a network experiment be designed to achieve high statistical power? Experimental treatments on networks may spread. Randomizing assignment of treatment to nodes enhances learning about the counterfactual causal effects of a social network experiment and also requires new methodology (ex. Aronow and Samii, 2017a, Bowers et al., 2013, Toulis and Kao, 2013). In this paper we show that the way in which a treatment propagates across a social network affects the statistical power of an experimental design. As such, prior information regarding treatment propagation should be incorporated into the experimental design. Our findings justify reconsideration of standard practice in circumstances where units are presumed to be independent even in simple experiments: information about treatment effects is not maximized when we assign half the units to treatment and half to control. We also present an example in which statistical power depends on the extent to which the network degree of nodes is correlated with treatment assignment probability. We recommend that researchers think carefully about the underlying treatment propagation model motivating their study in designing an experiment on a network.     

Similarity in friendship networks: Selection or influence? The effect of constraining contexts and non-visible individual attributes

Most research on similarity in friendship networks focuses on clearly visible individual attributes (i.e. attitudes and behaviors) in contexts where choices whom to befriend are relatively unconstrained. These studies often reveal that social selection rather than social influence is the dominant cause of similarity among friends. We argue that in a setting where social collaboration is crucial and friendship choices are more constrained, influence might be the main reason for similarity found among friends. In addition, we examined whether social categorization and peer control amplifies the social influence process among friends. Using a stochastic actor-based model for network dynamics, we analyzed a three-wave dataset of first year Royal Netherlands Naval College officer students on friendship formation and military discipline. The data supports our first hypothesis that students adjust their own military discipline to that of their friends. Contrary to our expectations, we did not find support for the idea that individuals adjust their discipline more to friends who are of the same military specialty, and neither more to friends who exert peer control. We elaborate on these findings in the discussion.     

The role of network setting and gender in online content popularity

In this study, we explore the role of specific network structures that enhance social capital and assess the extent to which gender, social ties, and communication interaction relate to content popularity within online social networks (OSNs). Our results are based on an extensive OSN data set, containing over 100,000 members, connected by over 1.7 million links. The findings indicate that content popularity inference is more accurate when considering activity interaction among users and that network structures known as advantageous for amassing social capital in the offline environment are relevant online as well. We conclude by discussing how gender mediates the correlation between some network measures and the growth of users’ content popularity and provide a potential explanation for the emergence of gender differences.     

Neighborhood–Based Models For Social Networks

We argue that social networks can be modeled as the outcome of processes that occur in overlapping local regions of the network, termed local social neighborhoods. Each neighborhood is conceived as a possible site of interaction and corresponds to a subset of possible network ties. In this paper, we discuss hypotheses about the form of these neighborhoods, and we present two new and theoretically plausible ways in which neighborhood–based models for networks can be constructed. In the first, we introduce the notion of a setting structure, a directly hypothesized (or observed) set of exogenous constraints on possible neighborhood forms. In the second, we propose higher–order neighborhoods that are generated, in part, by the outcome of interactive network processes themselves. Applications of both approaches to model construction are presented, and the developments are considered within a general conceptual framework of locale for social networks. We show how assumptions about neighborhoods can be cast within a hierarchy of increasingly complex models; these models represent a progressively greater capacity for network processes to "reach" across a network through long cycles or semipaths. We argue that this class of models holds new promise for the development of empirically plausible models for networks and network–based processes.     

Group based trajectories of network formation and dynamics

In this paper, we propose the application of a semi-parametric statistical methodology called Group-Based Developmental Trajectory Analysis to studying the dynamics of social networks. We begin with a discussion of theoretical problems in network analysis that may benefit from this approach. Next, we describe the methodology and how it can be applied to dyadic network data as well as aggregated node level data. We then demonstrate the methodology by analyzing the Newcomb Fraternity and the van de Bunt student data sets. Finally, we conclude with a discussion of potential directions for further research.     

Consumer Culture,Taste Preferences,and Social Network Formation

One of the most important and consistent findings in the social networks literature is that individuals are socially connected to people who resemble themselves. This finding extends to preferences for consumer culture. Whereas network theorists previously had presumed that social networks generated this outcome through a process of social influence, this traditional conception of the relationship between culture and social networks has been challenged by new theoretical perspectives and novel methodological techniques that enable researchers to empirically test the causal direction of the relationship. In this article, I first discuss how theorists have adjudicated between competing explanations of the relationship of taste preferences and social network structure. Second, I discuss how sociologists have theorized that tastes contribute to variation in network structure. Third, I examine survey and ethnographic research that discusses interactional mechanisms by which people actively mobilize culture to form social relationships. Fourth and finally, I discuss research that explores how consumer culture constitutes the meaning of social relationships and how relationship category affects theorizing of network formation.     

Multilevel meta network analysis with application to studying network dynamics of network interventions

In this paper, I introduce new methods for multilevel meta network analysis. The new methods can combine results from multiple network models, assess the effects of predictors at network or higher levels and account for both within- and cross-network correlations of the parameters in the network models. To demonstrate the new methods, I studied network dynamics of a smoking prevention intervention that was implemented in 76 classes of six middle schools in China. The results show that as compared to random intervention (i.e., that targets random students), smokers’ popularity was significantly reduced in the classes with network interventions (i.e., those target central students or students with their friends together). The findings highlight the importance of examining network outcomes in evaluating social and health interventions, the role of social selection in managing social influence, and the potential of using network methods to design more effective interventions.     

To tell the truth: Measuring concordance in multiply reported network data

Social network data must accurately reflect actors’ relationships to properly estimate network features. Here, we examine multiple reports of sexual, drug-sharing and social tie data on high-risk networks in Colorado Springs. By comparing multiple reports on the same ties, we can evaluate the reliability of this study's network data. Our findings suggest that these data have a high level of reporting agreement. From these findings, we discuss implications for analysis of these and similar data and provide suggestions for future social network data collection efforts.     

Extended structures of mediation: Re-examining brokerage in dynamic networks

In this paper we revisit the concept of brokerage in social networks. We elaborate on the concept of brokerage as a process, identifying three distinct classes of brokerage behavior. Based on this process model, we develop a framework for measuring brokerage opportunities in dynamic relational data. Using data on emergent inter-organizational collaborations, we employ the dynamic brokerage framework to examine the relationship between organizational attributes and coordination in the evolving network. Comparing the findings of our process-based definition with traditional, static approaches, we identify important dimensions of organizational action that would be missed by the latter approach.     

Relationships between Economics,Welfare, Social Network Factors,and Net Migration in the United States

By using economics, welfare and social network factors as frames of reference, this study aims to explore the relationship between these three factors and net migration to various US states. Adopting related variables collected from official aggregate data, this study first utilizes Logit Regression analysis to draw out seven variables that best explain net migration to the various states, then employs these variables in LISREL analyses to build a model explaining the factors influencing net migration to the various US states. Concretely, this research obtained the following findings: (1) the seven variables ‐‐ the average rate of net migrants of 2002–2005, Medicaid, federal aid, employment rate, non‐poverty population rate, and SSI subsidy ‐‐ all significantly affected (p < 0.01 or p < 0.05) net migration in 2006; (2) the main influences on net migration for the various states are, from highest to lowest, social network, economic, and welfare factors. More specifically, a better explanation is that, through the social network factor, economic and welfare factors exert an increased influence on the net number of migrants; and (3) as for the influence of social network factors on the number of net migrants, the social network factor for the previous year was found to best explain domestic migration flows, while the social network factor for the previous three‐to‐four years best explained international migration flows.     

Social class,social networks and variety of weak and strong practices

Most research on the structural foundations of cultural consumption views tastes and practices as a better or worse emanation of social class or status. In contrast, this paper shows that cultural consumption is also embedded in a larger system of social networks. Not only does it examine whether having more diversified personal network translates into being involved in a wider range of cultural activities (omnivorousness), it also tests whether holding networks of different strength corresponds with different levels of cultural engagement (strong vs. weak). Based on the survey data collected in Poland in 2017, the analyses yield three main findings. First, cultural consumption continues to reflect social class divisions and is a potential mechanism for social exclusion. Second, network diversity is associated with cultural variety independently of class position. Third, the number of weak ties people hold is more strongly associated with the number of “weak” practices (that is practices of less frequency) and the number of strong ties is positively associated with the number of strong practices (voraciousness). These findings are discussed in terms of balance theory, interactional foci and weak versus strong culture. The implications of the article are that omnivorism both signifies class boundaries and indicates participation in different network structures.     

How biology became social,and what it means for social theory

In this paper I first offer a systematic outline of a series of conceptual novelties in the life‐sciences that have favoured, over the last three decades, the emergence of a more social view of biology. I focus in particular on three areas of investigation: (1) technical changes in evolutionary literature that have provoked a rethinking of the possibility of altruism, morality and prosocial behaviours in evolution; (2) changes in neuroscience, from an understanding of the brain as an isolated data processor to the ultrasocial and multiply connected social brain of contemporary neuroscience; and (3) changes in molecular biology, from the view of the gene as an autonomous master of development to the ‘reactive genome’ of the new emerging field of molecular epigenetics. In the second section I reflect on the possible implications for the social sciences of this novel biosocial terrain and argue that the postgenomic language of extended epigenetic inheritance and blurring of the nature/nurture boundaries will be as provocative for neo‐Darwinism as it is for the social sciences as we have known them. Signs of a new biosocial language are emerging in several social‐science disciplines and this may represent an exciting theoretical novelty for twenty‐first social theory.     

Networks of Contention: The Shape of Online Transnationalism in Early Twenty-First Century Social Movement Coalitions

The study of new media use by transnational social movements is central to contemporary investigations of social contention. In order to shed light on the terrain in which the most recent examples of online mobilization have grown and developed, this paper combines the interest in the transnational dynamics of social contention and the exploration of the use of new information and communication technologies (ICTs) for protest action. In specific terms, the study investigates how early twenty-first century social movement coalitions used Internet tools to build symbolically transnational collective identities. By applying a hyperlink network analysis approach, the study focuses on a website network generated by local chapters of the World Social Forum (WSF), one of the earliest social movement coalitions for global justice. The sample network, selected through snowball sampling, is composed of 222 social forum websites from around the world. The study specifically looks at hyperlinks among social forum websites as signs of belonging and potential means of alliance. The analysis uses network measures, namely of cohesion, centrality, structural equivalence and homophily, to test dynamics of symbolic collective identification underlying the WSF coalition. The findings show that in early twenty-first century transnational contention, culture and place still played a central role in the emergence of transnational movement networks.     

Gender identity and lexical variation in social media

We present a study of the relationship between gender, linguistic style, and social networks, using a novel corpus of 14,000 Twitter users. Prior quantitative work on gender often treats this social variable as a female/male binary; we argue for a more nuanced approach. By clustering Twitter users, we find a natural decomposition of the dataset into various styles and topical interests. Many clusters have strong gender orientations, but their use of linguistic resources sometimes directly conflicts with the population‐level language statistics. We view these clusters as a more accurate reflection of the multifaceted nature of gendered language styles. Previous corpus‐based work has also had little to say about individuals whose linguistic styles defy population‐level gender patterns. To identify such individuals, we train a statistical classifier, and measure the classifier confidence for each individual in the dataset. Examining individuals whose language does not match the classifier's model for their gender, we find that they have social networks that include significantly fewer same‐gender social connections and that, in general, social network homophily is correlated with the use of same‐gender language markers. Pairing computational methods and social theory thus offers a new perspective on how gender emerges as individuals position themselves relative to audiences, topics, and mainstream gender norms.     

The Exclusiveness of the Political Field: Networks and political mobilization

This paper applies social network analysis to three case study social movement organizations based in the north of England: a local Labour Party branch, an environmental group, and a conservation group. Using a postal survey of members, we chart the extent of ties between members of these three groups, indicating how each group has its own internal social dynamics and characteristics that are related to the nature of the movement organizations themselves. We explore how the network structures interrelate with the socio-demographic structure of the membership of the three organizations, and we show there are important differences in the way that core members of the three organizations are recruited compared to those who are either peripheral or isolated. Our paper is the first to analyse the networks of whole populations of case study organizations in the UK, and can therefore be read as developing the potential of social network analysis for case study research and for understanding social movements. Analytically we argue it is important to distinguish two different types of ways that networks are important. They can be seen as offering resources for mobilization, or they can be seen as providing a means of integrating particular types of individuals into organizations. It is this latter sense that offers a more fundamental role for network analysis, and we argue that it offers an important way of developing insights from resource mobilization theory by relating them to Bourdieu's provocative arguments regarding the exclusiveness of the political field.     

The consumer litigation industry: Chasing dragon kings in lawyer–client networks

The community of lawyers and their clients form a scale-free bipartite network that develops naturally as the outcome of the recommendation process through which lawyers form their client base. This process is an example of preferential attachment where lawyers with more clients are more likely to be recommended to new clients. Consumer litigation is an important market for lawyers. In large consumer societies, there always a significant amount of consumption disputes that escalate to court. In this paper we analyze a dataset of thousands of lawsuits, reconstructing the lawyer–client network embedded in the data. Analyzing the degree distribution of this network we noticed that it follows that of a scale-free network built by preferential attachment, but for a few lawyers with much larger client base than could be expected by preferential attachment. Incidentally, most of these also figured on a list put together by the judiciary of lawyers which openly advertised the benefits of consumer litigation. According to the code of ethics of their profession, lawyers should not stimulate clients into litigation, but it is not strictly illegal. From a network formation point of view, this stimulation can be seen as a separate growth mechanism than preferential attachment alone. In this paper we find that this composite growth can be detected by a simple statistical test, as simulations show that lawyers which use both mechanisms quickly become the “dragon-kings” of the distribution of the number of clients per lawyer.     

Bridging,brokerage and betweenness

Valente and Fujimoto (2010) proposed a measure of brokerage in networks based on Granovetter's classic work on the strength of weak ties. Their paper identified the need for finding node-based measures of brokerage that consider the entire network structure, not just a node's local environment. The measures they propose, aggregating the average change in cohesion for a node's links, has several limitations. In this paper we review their method and show how the idea can be modified by using betweenness centrality as an underpinning concept. We explore the properties of the new method and provide point, normalized, and network level variations. This new approach has two advantages, first it provides a more robust means to normalize the measure to control for network size, and second, the modified measure is computationally less demanding making it applicable to larger networks.     

Measuring social dynamics in a massive multiplayer online game

Quantification of human group-behavior has so far defied an empirical, falsifiable approach. This is due to tremendous difficulties in data acquisition of social systems. Massive multiplayer online games (MMOG) provide a fascinating new way of observing hundreds of thousands of simultaneously socially interacting individuals engaged in virtual economic activities. We have compiled a data set consisting of practically all actions of all players over a period of 3 years from a MMOG played by 300,000 people. This large-scale data set of a socio-economic unit contains all social and economic data from a single and coherent source. Players have to generate a virtual income through economic activities to ‘survive’ and are typically engaged in a multitude of social activities offered within the game. Our analysis of high-frequency log files focuses on three types of social networks, and tests a series of social-dynamics hypotheses. In particular we study the structure and dynamics of friend-, enemy- and communication networks. We find striking differences in topological structure between positive (friend) and negative (enemy) tie networks. All networks confirm the recently observed phenomenon of network densification. We propose two approximate social laws in communication networks, the first expressing betweenness centrality as the inverse square of the overlap, the second relating communication strength to the cube of the overlap. These empirical laws provide strong quantitative evidence for the Weak ties hypothesis of Granovetter. Further, the analysis of triad significance profiles validates well-established assertions from social balance theory. We find overrepresentation (underrepresentation) of complete (incomplete) triads in networks of positive ties, and vice versa for networks of negative ties. Empirical transition probabilities between triad classes provide evidence for triadic closure with extraordinarily high precision. For the first time we provide empirical results for large-scale networks of negative social ties. Whenever possible we compare our findings with data from non-virtual human groups and provide further evidence that online game communities serve as a valid model for a wide class of human societies. With this setup we demonstrate the feasibility for establishing a ‘socio-economic laboratory’ which allows to operate at levels of precision approaching those of the natural sciences.All data used in this study is fully anonymized; the authors have the written consent to publish from the legal department of the Medical University of Vienna.     

Social network capital, economic mobility and poverty traps

This paper explores the role social network capital might play in facilitating poor agents?? escape from poverty traps. We model and simulate endogenous link formation among households heterogeneously endowed with both traditional and social network capital who make investment and technology choices over time in the absence of financial markets and faced with multiple production technologies featuring different fixed costs and returns. We show that social network capital can either complement or substitute for productive assets in facilitating some poor households?? escape from poverty. However, the voluntary nature of costly link formation also creates exclusionary mechanisms that impede some poor households?? use of social network capital. Through numerical simulation, we show that the ameliorative potential of social networks therefore depends fundamentally on the broader socio-economic wealth distribution in the economy, which determines the feasibility of social interactions and the net intertemporal benefits resulting from endogenous network formation. In some settings, targeted public transfers to the poor can crowd-in private resources by inducing new social links that the poor can exploit to escape from poverty.