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.     

Micro-structural foundations of network inequality: Evidence from a field experiment in professional networking

Sociological accounts of network inequality typically rely on the logic of preferential attachment, holding that individuals in a social network prefer to form ties with central rather than peripheral actors. We develop an alternative explanation for the growth of network inequality that does not require actors to have knowledge about the social position of others or to hold explicit preferences for partners based on such knowledge. Instead, we theorize that central actors benefit from being exposed to more opportunities for triadic closure, which confounds a quality- or popularity-based signal that their greater connectedness might also send. We test this prediction an observational study and a field experiment across multiple professional conferences. In the field experiment, we test whether network centrality is predictive of tie formation if the benefits that central actors receive through their disproportional exposure to second-order network neighbors are randomly suppressed. The findings demonstrate that for the same level of exposure to opportunities for triadic closure, central actors and less central actors are equally likely to be selected as network partners. We discuss how the proposed mechanism may be used to rectify social capital disadvantages among disadvantaged groups.     

Social context and network formation: An experimental study

Recently, there has been increasing interest in determining which social network structures emerge as a consequence of the conscious actions of actors. Motivated by the belief that “networks matter” in reaching personal objectives, it is a natural assumption that actors try to optimize their network position. Starting from the notion that an optimal network position depends on the social context, we examine how actors change their networks to reach better positions in various contexts. Distinguishing between three social contexts (a neutral context, a context in which closed triads are costly, and a context in which closed triads are beneficial), theoretical results predict that emerging networks are contingent on the incentives that are present in these contexts. Experiments are used to test whether networks that are theoretically predicted to be stable are also stable experimentally. We find that emerging networks correspond to a large extent with the predicted networks. Consequently, they are contingent on the incentives present in various social contexts. In addition, we find that subjects tend to form specific stable networks with a higher probability than predicted, namely, efficient networks and networks in which everyone is equally well off.     

How social exclusion distorts social network perceptions

In two studies we investigate whether social exclusion—a well-studied, common and quite painful social experience-influences people's perceptions of novel social networks. In a first study, exclusion experiences led people to report that novel networks were more dense relative to those who had not been excluded. As predicted, this was true only for social networks; exclusion had no impact on perceptions when networks were described as geographical. In a follow-up experiment, participants watched a custom-created video, depicting avatars interacting in social scenes and they were asked to report the ties among the avatars in the video. Exclusion experiences led people to see network ties where none exist (i.e., false positives), though there was no effect for exclusion (versus inclusion) on reports of false negatives. Results indicate that common social experiences systematically shape network perceptions, leading people to seeing novel social networks as more densely connected than they are.     

Modelling the evolution of a bipartite network—Peer referral in interlocking directorates

A central part of relational ties between social actors is constituted by shared affiliations and events. The action of joint participation reinforces personal ties between social actors as well as mutually shared values and norms that in turn perpetuate the patterns of social action that define groups. Therefore the study of bipartite networks is central to social science. Furthermore, the dynamics of these processes suggests that bipartite networks should not be considered static structures but rather be studied over time. In order to model the evolution of bipartite networks empirically we introduce a class of models and a Bayesian inference scheme that extends previous stochastic actor-oriented models for unimodal graphs. Contemporary research on interlocking directorates provides an area of research in which it seems reasonable to apply the model. Specifically, we address the question of how tie formation, i.e. director recruitment, contributes to the structural properties of the interlocking directorate network. For boards of directors on the Stockholm stock exchange we propose that a prolific mechanism in tie formation is that of peer referral. The results indicate that such a mechanism is present, generating multiple interlocks between boards.     

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.     

More or less guanxi: Trust is 60% network context, 10% individual difference

The strong ties known in China as guanxi can be distinguished by a high level of trust relatively independent of the surrounding social structure. Using network data from a stratified probability sample of 700 entrepreneurs citing 4664 contacts, we study guanxi relative to other relations to learn how much individual differences such as well-being, business differences, political participation and demographic factors matter for the guanxi distinction. Two findings stand out: First, the connection between trust and social network is robust to most differences between individuals, especially business and political differences. Trust variance is 60% network context, and 10% individual differences. Trust increases within a relationship as network closure increases around the relationship, but some relationships mature into guanxi ties within which trust is high and relatively independent of the surrounding social structure. Second, when individual differences matter, they concern social isolation. Guanxi ties are more distinct in the networks around entrepreneurs with small, marginal families, and around those with small, closed networks. Both categories of entrepreneurs are likely to experience difficulties with respect to resource access and doing business with people beyond their network, which may explain why longstanding guanxi ties linked to important events are particularly distinct for these entrepreneurs.     

Engagement of the Elderly in Time Banking: The Potential for Social Capital Generation in an Aging Society

Community currency systems attempt to empower the economically marginalized and build social capital. This research explores the role of the elderly in a local voluntary organization. The elderly are potentially very important contributors, yet we know little about their participation in these local exchange networks. Eighty-seven months' worth of transaction data from a “time bank,” which has had a total of 950 members, was examined in social network analyses. Measures of quantitative engagement in the system were constructed. The elderly were found to be as active as other members. Qualitative characteristics of the network were also explored. The organization is rather homogeneous, yet exchanges within it tend to connect diverse actors. Male and female seniors undertransact with themselves and with one another, generating bridging social capital. The evidence presented suggests that the participation of the elderly in local currencies is mutually beneficial.     

Network centrality and social movement media coverage: A two-mode network analytic approach

This article examines the relationship between structural location (namely, degree centrality) and news media coverage. Our central hypothesis is that the network centrality of social movement actors is positively associated with the prevalence of actors being cited in the print news media. This paper uses two-mode data from a communication network of environmentalists in British Columbia, and examines the relationship between their structural location and the frequency by which they are cited in newsprint media with regard to particular frames (about forest conservation, environmental protest, and related issues). We asked a sample of social movement participants about their ties to a target list of relatively high profile actors (environmental activists). We turned the resulting network matrix into a bipartite graph that examined the relationships amongst the target actors vis a vis the respondents. Next we calculated point in-degree for the target actors. For the target actors we also have data from a representative sample of 957 print news articles about forestry and conservation of old growth forests in British Columbia. We compare the effects of network centrality of the target actor versus several attributes of the target actors (gender, level of radicalism, leadership status) on the amount of media coverage that each of the target actors receives. We find that network centrality is associated with media coverage controlling for actor attributes. We discuss theoretical implications of this research. Finally, we also discuss the methodological pros and cons of using a “target name roster” to construct two-mode data on social movement activists.     

Introduction to stochastic actor-based models for network dynamics

Stochastic actor-based models are models for network dynamics that can represent a wide variety of influences on network change, and allow to estimate parameters expressing such influences, and test corresponding hypotheses. The nodes in the network represent social actors, and the collection of ties represents a social relation. The assumptions posit that the network evolves as a stochastic process ‘driven by the actors’, i.e., the model lends itself especially for representing theories about how actors change their outgoing ties. The probabilities of tie changes are in part endogenously determined, i.e., as a function of the current network structure itself, and in part exogenously, as a function of characteristics of the nodes (‘actor covariates’) and of characteristics of pairs of nodes (‘dyadic covariates’). In an extended form, stochastic actor-based models can be used to analyze longitudinal data on social networks jointly with changing attributes of the actors: dynamics of networks and behavior.     

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.     

Residential mobility and the spatial dispersion of personal networks: Effects on social support

Using a representative national sample of personal networks, this article explores how the spatial dispersion of networks, residential mobility and social support are linked. Three issues will be addressed here. Firstly, how is the spatial dispersion of personal networks related to individuals’ social characteristics, network composition and residential mobility? Secondly, how do the spatial dispersion of networks, residential mobility and their combined effect influence the number and (thirdly) the structure of emotional support ties? Results showed that the extent of the support was affected neither by the geographical distribution of the networks nor by residential mobility. Living far from one's birthplace, however, exerted two distinct, and opposite effects on the support network structure. On the one hand, mobility led to high spatial dispersion of personal contacts, which in turn favored a sparsely knit network centered around the mobile individual. On the other hand, by controlling for the effect of distance between the contacts, we found that individuals that cited long-distance ties tended to be part of more transitive support networks than those that cited local ties. We interpreted the latter effect as evidence that transitive ties may survive greater spatial distances than intransitive ones. These findings are discussed in view of spatial mobility and social network research.     

Logit Models for Affiliation Networks

Once confined to networks in which dyads could be reasonably assumed to be independent, the statistical analysis of network data has blossomed in recent years. New modeling and estimation strategies have made it possible to propose and evaluate very complex structures of dependency between and among ties in social networks. These advances have focused exclusively on one-mode networks—that is, networks of direct ties between actors. We generalize these models to affiliation networks, networks in which actors are tied to each other only indirectly through belonging to some group or event. We formulate models that allow us to study the (log) odds of an actor's belonging to an event (or an event including an actor) as a function of properties of the two-mode network of actors' memberships in events. We also provide illustrative analysis of some classic data sets on affiliation networks.     

‘We've Also Become Quite Good Friends’: Environmentalists,Social Networks and Social Comparison in British Columbia,Canada

Social networks influence social movement recruitment and individuals' ongoing participation in social movement organizations. In this article, we use a qualitative approach to explore the meaning of social networks for environmental movement participants in British Columbia, Canada. Our analysis draws on interviews with 33 core members of the movement. Environmental group participation creates multiplex social networks, encompassing work, leisure and friendship. Social movement networks are conduits for information exchange among environmental groups and they amplify the political power of individual participants. Ties to government workers and forest company management are more intense – based on frequency of contact – than ties to forestry labour or First Nations groups. However, forestry workers and First Nations are viewed more positively than government or forest company management. This illustrates how the intensity of social network ties can be distinguished from the subjective meanings attached to them by network participants.     

Prismatic effects of negative ties

Research on negative ties has focused primarily on the harm they do. In this paper, we show that negative ties can also have beneficial effects. We argue that, like positive ties, negative ties can link actors together in the minds of observers. As a result, we theorize that negative ties with high-status actors can benefit a focal actor, whereas negative ties with low-status actors can harm the focal actor. This prismatic effect depends on the existing status of the focal actor: a focal actor of low status is likely to benefit far more from negative ties with high-status actors and suffer more from negative ties with low-status actors than will an actor of high-status. To test our ideas, we analyze the phenomenon of "diss songs" in hip-hop music. A diss song is a song in which a rapper makes derogatory comments about another rapper, constituting a negative tie. We analyze the effects of negative ties among 53 rappers over 20 points in time on audience reaction as measured by record sales. We find that negative ties with high-status actors enhance future sales for low-status actors. However, negative ties with lower-status actors have no effect on the future sales of both low- and high-status actors. Just as some researchers have reported both positive and negative consequences of social capital, our study demonstrates that negative ties can also have both positive and negative outcomes.     

How social ties contribute to collective actions on social media: A social capital approach

In public relations research into civic engagement, the influence of social ties on the individual level has not been adequately studied from a social capital perspective. To fill this gap, this study conducts a one-factor between subjects experiment to examine the difference, if any, between the social influence of strong ties and of weak ties on individuals’ participation intentions in regard to collective actions. This study postulates collective efficacy as a factor possibly associated with the intention to participate in collective actions. The study findings suggest that advocacy about certain social causes, such as veterans affairs, have globally positive effects on publics’ civic engagement intentions, regardless of the norms of the social network with which the individuals are connected. Furthermore, collective efficacy was found to be positively associated with participation in collective actions. The theoretical and practical implications of these findings are discussed.     

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.     

Judgment of distributional inequality in networks

Why is income inequality perceived and judged differently across a society? Following the social comparison theory, one reasonable explanation suggests that individuals are exposed to different local reference groups in social networks. We design a vignette experiment to study how income distributions are judged by individuals structured in networks. The experiment shows that perceptions of distributional inequality are high when network ties are unequally distributed across individuals, suggesting that network inequality contributes to distributional inequality. Beyond the network effect, inequality judgment is found to be driven by a mix of self-interest and other-regarding preference: people are in favor of group-beneficial income distributions wherein they rank high, but not extremely high, in the group. It shows that people care about not only their relative affluence, but also where others stand in the distribution.     

A network centrality bias: Central individuals in workplace networks have more supportive coworkers

Combining the results of two empirical studies, we investigate the role of alters’ motivation in explaining change in ego’s network position over time. People high in communal motives, who are prone to supportive and altruistic behavior in their interactions with others as a way to gain social acceptance, prefer to establish ties with co-workers occupying central positions in organizational social networks. This effect results in a systematic network centrality bias: The personal network of central individuals (individuals with many incoming ties from colleagues) is more likely to contain more supportive and altruistic people than the personal network of individuals who are less central (individuals with fewer incoming ties). This result opens the door to the possibility that the effects of centrality so frequently documented in empirical studies may be due, at least in part, to characteristics of the alters in an ego’s personal community, rather than to egos themselves. Our findings invite further empirical research on how alters’ motives affect the returns that people can reap from their personal networks in organizations.