The structure of online social networks mirrors those in the offline world

We use data on frequencies of bi-directional posts to define edges (or relationships) in two Facebook datasets and a Twitter dataset and use these to create ego-centric social networks. We explore the internal structure of these networks to determine whether they have the same kind of layered structure as has been found in offline face-to-face networks (which have a distinctively scaled structure with successively inclusive layers at 5, 15, 50 and 150 alters). The two Facebook datasets are best described by a four-layer structure and the Twitter dataset by a five-layer structure. The absolute sizes of these layers and the mean frequencies of contact with alters within each layer match very closely the observed values from offline networks. In addition, all three datasets reveal the existence of an innermost network layer at ∼1.5 alters. Our analyses thus confirm the existence of the layered structure of ego-centric social networks with a very much larger sample (in total, >185,000 egos) than those previously used to describe them, as well as identifying the existence of an additional network layer whose existence was only hypothesised in offline social networks. In addition, our analyses indicate that online communities have very similar structural characteristics to offline face-to-face networks.     

Assessing structural correlates to social capital in Facebook ego networks

Research in computer-mediated communication has consistently asserted that Facebook use is positively correlated with social capital. This research has drawn primarily on Williams’ (2006) bridging and bonding scales as well as behavioral attributes such as civic engagement. Yet, as social capital is inherently a structural construct, it is surprising that so little work has been done relating social capital to social structure as captured by social network site (SNS) Friendship networks. Facebook is particularly well-suited to support the examination of structure at the ego level since the networks articulated on Facebook tend to be large, dense, and indicative of many offline foci (e.g., coworkers, friends from high school). Assuming that each one of these foci only partially overlap, we initially present two hypotheses related to Facebook social networks and social capital: more foci are associated with perceptions of greater bridging social capital and more closure is associated with greater bonding social capital. Using a study of 235 employees at a Midwestern American university, we test these hypotheses alongside self-reported measures of activity on the site. Our results only partially confirm these hypotheses. In particular, using a widely used measure of closure (transitivity) we observe a strong and persistent negative relationship to bonding social capital. Although this finding is initially counter-intuitive it is easily explained by considering the topology of Facebook personal networks: networks with primarily closed triads tend to be networks with tightly bound foci (such as everyone from high school knowing each other) and few connections between foci. Networks with primarily open triads signify many crosscutting friendships across foci. Therefore, bonding social capital appears to be less tied to local clustering than to global cohesion.     

Analysing networks of networks

We consider data with multiple observations or reports on a network in the case when these networks themselves are connected through some form of network ties. We could take the example of a cognitive social structure where there is another type of tie connecting the actors that provide the reports; or the study of interpersonal spillover effects from one cultural domain to another facilitated by the social ties. Another example is when the individual semantic structures are represented as semantic networks of a group of actors and connected through these actors’ social ties to constitute knowledge of a social group. How to jointly represent the two types of networks is not trivial as the layers and not the nodes of the layers of the reported networks are coupled through a network on the reports. We propose to transform the different multiple networks using line graphs, where actors are affiliated with ties represented as nodes, and represent the totality of the different types of ties as a multilevel network. This affords studying the associations between the social network and the reports as well as the alignment of the reports to a criterion graph. We illustrate how the procedure can be applied to studying the social construction of knowledge in local flood management groups. Here we use multilevel exponential random graph models but the representation also lends itself to stochastic actor-oriented models, multilevel blockmodels, and any model capable of handling multilevel networks.     

How to search a social network

We address the question of how participants in a small world experiment are able to find short paths in a social network using only local information about their immediate contacts. We simulate such experiments on a network of actual email contacts within an organization as well as on a student social networking website. On the email network we find that small world search strategies using a contact’s position in physical space or in an organizational hierarchy relative to the target can effectively be used to locate most individuals. However, we find that in the online student network, where the data is incomplete and hierarchical structures are not well defined, local search strategies are less effective. We compare our findings to recent theoretical hypotheses about underlying social structure that would enable these simple search strategies to succeed and discuss the implications to social software design.     

Exponential random graph models for little networks

Statistical models for social networks have enabled researchers to study complex social phenomena that give rise to observed patterns of relationships among social actors and to gain a rich understanding of the interdependent nature of social ties and actors. Much of this research has focused on social networks within medium to large social groups. To date, these advances in statistical models for social networks, and in particular, of Exponential-Family Random Graph Models (ERGMS), have rarely been applied to the study of small networks, despite small network data in teams, families, and personal networks being common in many fields. In this paper, we revisit the estimation of ERGMs for small networks and propose using exhaustive enumeration when possible. We developed an R package that implements the estimation of pooled ERGMs for small networks using Maximum Likelihood Estimation (MLE), called “ergmito”. Based on the results of an extensive simulation study to assess the properties of the MLE estimator, we conclude that there are several benefits of direct MLE estimation compared to approximate methods and that this creates opportunities for valuable methodological innovations that can be applied to modeling social networks with ERGMs.     

Cross-border credit networks,banking risk contagion and suppression effects

From the perspective of risk contagion, it is difficult to balance the benefits and costs of banking globalization. We use data on cross-border syndicated loans intended to build heterogeneous credit networks among banking sectors in various countries to explore the introduction of banking risks into the network. Via social network analysis (SNA), we find that the global credit network has phased characteristics, and it is a source of exposure to global banking risks. However, the more important network position, that is, the greater centrality, identified shows that the banking industry is more stable. To explain these findings, we present and estimate the banking risk contagion model and the suppression effect model of contagion. Evidence suggests that the international credit network is the channel of risk contagion, and the long-term loan network and nonfinancial borrower network have a stronger contagion effect. Exogenous banking supervision and network endogenous closeness centrality can inhibit risk contagion. From a policy perspective, these findings indicate the need to supervise high-risk cross-border loans and maintain independence in the international credit network.Data Availability StatementThe data that support the findings of this study are available from the corresponding author, [Heng Zhao, email: zhao0501@mail.dlut.edu.cn], upon reasonable request.     

Partitioning signed social networks

Structural balance theory has proven useful for delineating the blockmodel structure of signed social networks. Even so, most of the observed signed networks are not perfectly balanced. One possibility for this is that in examining the dynamics underlying the generation of signed social networks, insufficient attention has been given to other processes and features of signed networks. These include: actors who have positive ties to pairs of actors linked by a negative relation or who belong to two mutually hostile subgroups; some actors that are viewed positively across the network despite the presence of negative ties and subsets of actors with negative ties towards each other. We suggest that instead viewing these situations as violations of structural balance, they can be seen as belonging to other relevant processes we call mediation, differential popularity and internal subgroup hostility. Formalizing these ideas leads to the relaxed structural balance blockmodel as a proper generalization of structural balance blockmodels. Some formal properties concerning the relation between these two models are presented along with the properties of the fitting method proposed for the new blockmodel type. The new method is applied to four empirical data sets where improved fits with more nuanced interpretations are obtained.     

Assessing the bias in samples of large online networks

We consider the sampling bias introduced in the study of online networks when collecting data through publicly available APIs (application programming interfaces). We assess differences between three samples of Twitter activity; the empirical context is given by political protests taking place in May 2012. We track online communication around these protests for the period of one month, and reconstruct the network of mentions and re-tweets according to the search and the streaming APIs, and to different filtering parameters. We find that smaller samples do not offer an accurate picture of peripheral activity; we also find that the bias is greater for the network of mentions, partly because of the higher influence of snowballing in identifying relevant nodes. We discuss the implications of this bias for the study of diffusion dynamics and political communication through social media, and advocate the need for more uniform sampling procedures to study online communication.     

Boundary maintenance in support networks

Most studies of social networks, whether they are viewed as the context of stressful experiences or of supportive interactions, assume fixed network boundaries. This assumption is necessary in order to analyze structural characteristics such as network density. Actual networks, however, change over time and across situations and the assumption of fixed boundaries is inappropriate for processual questions. Examination of such changes reveals limitations in the structural analysis of social networks and points to mechanisms and strategies by which network boundaries are drawn and redrawn.     

Question-order effects in social network name generators

Social network surveys are an important tool for empirical research in a variety of fields, including the study of social capital and the evaluation of educational and social policy. A growing body of methodological research sheds light on the validity and reliability of social network survey data regarding a single relation, but much less attention has been paid to the measurement of multiplex networks and the validity of comparisons among criterion relations. In this paper, we identify ways that surveys designed to collect multiplex social network data might be vulnerable to question-order effects. We then test several hypotheses using a split-ballot experiment embedded in an online multiple name generator survey of teachers’ advice networks, collected for a study of complete networks. We conclude by discussing implications for the design of multiple name generator social network surveys.     

Actors and networks as objects

This paper explores the application of two contemporary computational methods to the development of sociological theory. Specifically, we combine the methods of object-orientation with discrete event simulation. This approach has several advantages for constructing and evaluating dynamic social theories.In object-oriented program design, objects combine and integrate the traditional concepts of data structures and algorithms, the building blocks of structured programming. Algorithms associated with objects are called methods or member functions. Constructing social actors as objects involves defining both their data attributes and the methods associated with these attributes. We also treat a social network as a computational object. It has data types of nodes and ties. As an object, the network must also have methods that add and delete nodes and ties. Once a network exists, we can create other data types and methods that describe and analyze the network. For example, networks have in-degree and out-degree vectors, and measures of hierarchy. In principle, we can create attributes of networks for all of the structural measures we use to describe networks.We use actor and network objects in a discrete event simulation of a process of formation of dominance structures, exploring several dynamic variations of the underlying theoretical model.     

Goal specific social capital and job satisfaction: Effects of different types of networks on instrumental and social aspects of work

This paper addresses the question “To what extent can job satisfaction be explained as the revenue of social capital?” By conceiving someone’s social network as social capital we specify conditions under which social ties do lead to job satisfaction. We inquire into the idea of goal specificity of social capital, which implies that a network with a given structure and content will have different impacts on various aspects of job satisfaction. If the content of the ties and the structure of the network at the job engender material well-being or produce social approval, satisfaction with the corresponding job aspects increases. Data were collected in 1993 using written questionnaires in two Dutch governmental agencies, one with 32 and the other with 44 employees. These workers’ networks were charted using nine name-generating questions.Social capital, it turns out, is not an all-purpose good but one that is goal specific, even within a single domain of life such as work. Three effects stand out: First, the structure of the network and the content of the ties do matter. Networks of strategic, work-related ties promote an employee’s satisfaction with instrumental aspects of the job, like income, security, and career opportunities. Second, closed networks of identity-based solidarity ties improve an employee’s satisfaction with social aspects of the job, like the general social climate at work and cooperation with management and colleagues. Third, a network with a bow–tie structure (i.e., where a focal actor is the link between two or more mutually exclusive cliques) generally has strong negative effects on satisfaction with the social side of the job; although a bow–tie type network of trusting ties does increase satisfaction with the social side. This implies that Krackhardt’s hypothesis on the unpleasant feelings produced by bow–tie type networks has to be specified for the content of the ties that constitute such a network. The most important conclusion of our analysis is that goal specificity of social capital has implications for both structure and content of social networks. Achievement of a particular goal, such as satisfaction at work, requires not only networks of a certain structure or ties with a particular content, but specifically structured networks of ties with a particular content.     

Mobility types,transnational ties and personal networks in four highly skilled immigrant communities in Seville (Spain)

In this study, we explore how different mobility patterns influence the composition and structure of the transnational social support networks and how personal networks allow us to elicit insightful data of mobile individuals. Ninety-five mobile individuals were selected from four distinct communities based in Seville (Spain), namely: Erasmus students, Flamenco artists, musicians from the symphonic orchestra and partners of European Commission researchers. Data were collected through an electronic survey sent by email with multiple name generators and a structured face-to-face interview utilizing a network visualization tool, VennMaker. Two distinct methods, namely qualitative case studies and cluster analysis were used to characterize mobility types. Findings reveal a heterogeneous foreign population, in which different forms of mobility are reflected in the personal networks of mobile individuals. Respondents who were settled in the city were more likely to have networks in which social support was mainly derived by hosts and people in the host location and with whom they communicated predominantly through face-to-face communication. Those who were in the host location for a study exchange, knowing that return to the county of origin is imminent were more likely to have networks linked to the home location. They relied heavily on strong transnational ties in the home country using social media to sustain their relationship. Respondents with an itinerant mobility profile, also had networks dominated by strong transnational ties, however, such ties had a higher degree of geographical spread due to previous international mobility. Participants who had a high number of hosts in the network but low connection between the ties were more likely to be linked to a specific subculture in the host society. The integration in the host location follows a different pattern to other settled individuals, mainly because their connection in the city tends to be community specific.     

Non-response in social networks: The impact of different non-response treatments on the stability of blockmodels

Discerning the essential structure of social networks is a major task. Yet, social network data usually contain different types of errors, including missing data that can wreak havoc during data analyses. Blockmodeling is one technique for delineating network structure. While we know little about its vulnerability to missing data problems, it is reasonable to expect that it is vulnerable given its positional nature. We focus on actor non-response and treatments for this. We examine their impacts on blockmodeling results using simulated and real networks. A set of ‘known’ networks are used, errors due to actor non-response are introduced and are then treated in different ways. Blockmodels are fitted to these treated networks and compared to those for the known networks. The outcome indicators are the correspondence of both position memberships and identified blockmodel structures. Both the amount and type of non-response, and considered treatments, have an impact on delineated blockmodel structures.     

The co-evolution of gossip and friendship in workplace social networks

This study investigates the co-evolution of friendship and gossip in organizations. Two contradicting perspectives are tested. The social capital perspective predicts that friendship causes gossip between employees, defined as informal evaluative talking about absent colleagues. The evolutionary perspective reverses this causality claiming that gossiping facilitates friendship. The data comprises of three observations of a complete organizational network, allowing longitudinal social network analyses. Gossip and friendship are modeled as both explanatory and outcome networks with RSiena. Results support the evolutionary perspective in that gossip between two individuals increases the likelihood of their future friendship formation. However, individuals with disproportionately high gossip activity have fewer friends in the network, suggesting that the use of gossiping to attract friends has a limit.     

Transnational issue networks in real and virtual space: the case of women,peace and security

To what extent do online issue networks serve as a proxy for their real‐space counterparts in structure and substance? This question is significant because a number of scholars have begun to study transnational advocacy networks through their representations online. We explored whether this assumption is valid by comparing the network composition and agenda composition of the advocacy network around ‘women, peace and security’, as operationalized through a web‐based survey of actual activists, and the network's online representations of itself, as measured through advocacy websites. Two specific concerns drove the study. First, how closely does the structure of issue networks, as represented on the World Wide Web, correspond with actual advocates' understanding of the players within a specific issue domain? Second, to what extent does the online issue agenda correlate with the most prominent issues described by real‐space advocates within a transnational network? Our findings yielded a high correlation between the online issue agenda and activists’ interpretations of the agenda. However, we found that while hyperlink analysis is an effective tool for identifying the ‘hubs’ or ‘gatekeepers’ within a specific issue network, the nature of the World Wide Web makes it is a blunt tool with which to capture the broader network. This suggests that while the web poses important opportunities as a data source, scholars of transnational networks must pay closer attention to the methodological assumptions implicit in their reliance on this and other new media.     

The stability of exchange networks

Economic and sociological exchange theories predict divisions of exchange benefits given an assumed fixed network of exchange relations. Since network structure has been found to have a large impact on actors’ payoffs, actors have strong incentives for network change. We answer the question what happens to both the network structure and actor payoffs when myopic actors change their links in order to maximize their payoffs. We investigate the networks that are stable, the networks that are efficient or egalitarian with varying tie costs, and the occurrence of social dilemmas. Only few networks are stable over a wide range of tie costs, and all of them can be divided into two types: efficient networks consisting of only dyads and at most one isolate, and Pareto efficient and egalitarian cycles with an odd number of actors. Social dilemmas are observed in even-sized networks at low tie costs.     

Who are the objects of positive and negative gossip at work?: A social network perspective on workplace gossip

Gossip is informal talking about colleagues. Taking a social network perspective, we argue that group boundaries and social status in the informal workplace network determine who the objects of positive and negative gossip are. Gossip networks were collected among 36 employees in a public child care organization, and analyzed using exponential random graph modeling (ERGM). As hypothesized, both positive and negative gossip focuses on colleagues from the own gossiper's work group. Negative gossip is relatively targeted, with the objects being specific individuals, particularly those low in informal status. Positive gossip, in contrast, is spread more evenly throughout the network.