Effects of missing data in social networks

We perform sensitivity analyses to assess the impact of missing data on the structural properties of social networks. The social network is conceived of as being generated by a bipartite graph, in which actors are linked together via multiple interaction contexts or affiliations. We discuss three principal missing data mechanisms: network boundary specification (non-inclusion of actors or affiliations), survey non-response, and censoring by vertex degree (fixed choice design), examining their impact on the scientific collaboration network from the Los Alamos E-print Archive as well as random bipartite graphs. The simulation results show that network boundary specification and fixed choice designs can dramatically alter estimates of network-level statistics. The observed clustering and assortativity coefficients are overestimated via omission of affiliations or fixed choice thereof, and underestimated via actor non-response, which results in inflated measurement error. We also find that social networks with multiple interaction contexts may have certain interesting properties due to the presence of overlapping cliques. In particular, assortativity by degree does not necessarily improve network robustness to random omission of nodes as predicted by current theory.     

Network constraints on social action: preliminaries for a network theory

The network approach to social reality lacks a theoretical body that backs up the assumption of the working of structural rules. This contribution is an attempt toward investigation of the possibility of a theory of the effects of network properties on social action. The structure and effects of social networks vary along with the aims put forward in the relations of which they are composed. Considering those aims, three different sorts of networks can be distinguished — sentiment-, interest- and power-networks — involving distinct action logics. When the nature of the ties is known, predictions about the structure of the resulting social networks, type of social control and type of exchange taking place within them, can be made.     

The Emergence and Stability of Groups in Social Networks

An important puzzle in social network research is to explain how macro-level structures emerge from micro-level network processes. Explaining the emergence and stability of structural groups in social networks is particularly difficult for two reasons. First, because groups are characterized both by high connectedness within (group cohesion) and lack of connectedness between them (group boundaries). Second, because a large number of theoretical micro-level network processes contribute to their emergence. We argue that traditional social network theories that are concerned with the evolution of positive relations (forces of attraction) are not sufficient to explain the emergence of groups because they lack mechanisms explaining the emergence of group boundaries. Models that additionally account for the evolution of negative ties (forces of repulsion) may be better suited to explain the emergence and stability of groups. We build a theoretical model and illustrate its usefulness by fitting stochastic actor-oriented models (SAOMs) to empirical data of co-evolving networks of friendship and dislike among 479 secondary-school students. The SAOMs include a number of newly developed effects expressing the co-evolution between positive and negative ties. We then simulate networks from the estimated models to explore the micro-macro link. We find that a model that considers forces of attraction and repulsion simultaneously is better at explaining groups in social networks. In the long run, however, the empirically informed simulations generate networks that are too stylized to be realistic, raising further questions about model degeneracy and time heterogeneity of group processes.     

Shared contexts and triadic closure in core discussion networks

This paper inquires into structural explanations for triadic closure in networks of confidants with whom one discusses important personal matters. Building upon the assumption that meeting opportunities affect network characteristics, we primarily argue that the social contexts in which network members meet, substantially affect triadic closure. The main empirical findings are (a) that about sixty percent of the triads in core discussion networks are closed triads, which also means that a substantial part of one's strong relations is unconnected, and (b) that meeting network members in the same social contexts is an important condition for, but certainly does not guarantee triadic closure. Importantly, the specific characteristics of social contexts explain why sharing certain contexts positively affects triadic closure, while sharing other contexts does not.     

A comparison of email networks and off-line social networks: A study of a medium-sized bank

Recently there has been a surge in the availability of online data concerning the connections between people, and these online data are now widely used to map the social structure of communities. There has been little research, however, on how these new types of relational data correspond to classical measures of social networks. To fill this gap, we contrast the structure of an email network with the underlying friendship, communication, and advice seeking networks. Our study is an explorative case study of a bank, and our data contains emails among employees and a survey of the ego networks of the employees. Through calculating correlations with QAP standard errors and estimating exponential random graph (ERG) models, we find that although the email network is related to the survey-based social networks, email networks are also significantly different: while off-line social networks are strongly shaped by gender, tenure, and hierarchical boundaries, the role of these boundaries are much weaker in the email network.     

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 social ties transcend class boundaries? Network variability as tool for exploring occupational homophily

The research on social network analysis established the existence of class homophily, the tendency that personal networks are homogeneous in the class sense, as one of the governing patterns. This is explained via two main mechanisms: choice homophily and induced homophily. But the literature focused less on the question how can class boundaries be transgressed and what are the channels of class heterophily. This paper explores class heterophily on Croatian data acquired through position generator, which measures social capital (resources captured in social relations) by exploring the range of different occupational positions which are accessible to an individual (extensity index). Network variability is thereby taken as proxy for class composition of personal networks. The paper concludes that that political participation and sociability enable cross-class ties, since this offers an opportunity to meet and befriend people from all walks of life; and that people on the middle of the social hierarchy have the most diverse social networks. The hypotheses that social mobility can represent a vehicle for class heterophily; and that class heterophily is more pronounced in smaller settlements, where society networks show more overlap between social circles; were confirmed only partially, and require further investigation. These findings concern class boundaries related to the notion of choice homophily. As for induced homophily, the paper concludes that here too the boundaries are not watertight, as cultural omnivores have a wider range of class contacts.     

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.     

Social Networks and Employment: Mechanisms (Part 1)

While substantial progress has recently been made in the literature on social networks and employment, this research has not been accompanied by a larger organizing framework. In this article, we attempt to provide such framework while reviewing the literature that addresses the context of work and employment from a social network perspective – that is, research based on the assumption that actors are embedded in networks of social relations and interactions. In particular, our review focuses on the primary mechanisms that help explain how networks may shape employment outcomes and processes, namely, by conveying resources and providing signals to others. Ties among social actors may transfer better or unique resources such as information, learning, influence, and support, which consequently may affect key employment outcomes. Ties may also provide signals concerning ability, legitimacy/trust, status, and relationship meaning. We conclude by presenting a number of alternative arguments in the literature and discussing future directions for the research on social networks and employment.     

Predictability of social connections over time

A developed theory of social networks would potentially provide predictive and explanatory models for social processes at the most general level. The paper contributes to such a theory by elaborating one basic proposition: that social connections attract each other as a regular function of network parameters such as ‘structural strength’ (number of common links) and ‘distance’ (length of minimal path of linkage). The proposition is tested on longitudinal data from three locality-based networks.     

Variations in network boundary and type: A study of adolescent peer influences

This study compares variation in network boundary and network type on network indicators such as degree and estimates of social influences on adolescent substance use. We compare associations between individual use and peer use of tobacco and alcohol when network boundary (e.g., classroom, entire grade in school, and community) and relational type (elicited by asking whom students: (a) are friends with, (b) admire, (c) think will succeed, (d) would like to have a romantic relationship with, and (e) think are popular) are varied. Additionally, we estimate Exponential Random Graph Models (ERGMs) for 232 networks to obtain a homophily estimate for smoking and drinking. Data were collected from a cross-sectional sample of 1707 adolescents in five high schools in one school district in Los Angeles, CA. Results of logistic regression models show that associations were strongest when the boundary condition was least constrained and that associations were stronger for friendship networks than for other ones. Additionally, ERGM estimations show that grade-level friendship networks returned significant homophily effects more frequently than the classroom networks. This study validates existing theoretical approaches to the network study of social influence as well as ways to estimate them. We recommend researchers use as broad a boundary as possible when collecting network data, but observe that for some research purposes more narrow boundaries may be preferred.     

VERY LOCAL STRUCTURE IN SOCIAL NETWORKS

Triadic configurations are fundamental to many social structural processes and provide the basis for a variety of social network theories and methodologies. This paper addresses the question of how much of the patterning of triads is accounted for by lower-order properties pertaining to nodes and dyads. The empirical base is a collection of 82 social networks representing a number of different species (humans, baboons, macaques, bison, cattle, goats, sparrows, caribou, and more) and an assortment of social relations (friendship, negative sentiments, choice of work partners, advice seeking, reported social interactions, victories in agonistic encounters, dominance, and co-observation). Methodology uses low dimensional representations of triad censuses for these social networks, as compared to censuses expected given four lower-order social network properties. Results show that triadic structure is largely accounted for by properties more local than triads: network density, nodal indegree and outdegree distributions, and the dyad census. These findings reinforce the observation that structural configurations that can be realized in empirical social networks are severely constrained by very local network properties, making some configurations extremely improbable.     

The complexity of social networks: theoretical and empirical findings

A great deal of work in recent years has been devoted to the topic of “complexity”, its measurement, and its implications. Here, the notion of algorithmic complexity is applied to the analysis of social networks. Structural features of theoretical importance — such as structural equivalence classes — are shown to be strongly related to the algorithmic complexity of graphs, and these results are explored using analytical and simulation methods. Analysis of the complexity of a variety of empirically derived networks suggests that many social networks are nearly as complex as their source entropy, and thus that their structure is roughly in line with the conditional uniform graph distribution hypothesis. Implications of these findings for network theory and methodology are also discussed.     

Fostering social capital in an international multi-stakeholder issue network

Scholars have theorized that public relations contributes to societies and communities by bringing attention to pressing public issues and fostering social capital in civil society networks. However, the extant research has studied civil society networks of NGOs, donors, and the media in transitional countries. This study extends the public relations model of civil society in two ways. First, it broadens the scope to an international context. Second, it draws from the multi-stakeholder issue network perspective to conceptualize a civil society network as a space where stakeholders of an issue mix their interests as they collectively address a pressing public issue. The literature on international and multi-stakeholder networks suggest that the international scope and the mixing of interests across sectors may restrict the production of social capital. The results from the social network analysis suggests that the mixing of interests across sectoral and geopolitical boundaries did not restrict the production of social capital. Rather, the patterns of the relationships among those on the core and those on the periphery of the network restricted the production of social capital. Such finding demonstrates how public relations’ functions like relationship building can have profound influences on social capital and civil society networks. The implications for public relations theorizing and research are discussed.     

Comparing Networks Across Space and Time, Size and Species

We describe and illustrate methodology for comparing networks from diverse settings. Our empirical base consists of 42 networks from four kinds of species (humans, nonhuman primates, nonprimate mammals, and birds) and covering distinct types of relations such as influence, grooming, and agonistic encounters. The general problem is to determine whether networks are similarly structured despite their surface differences. The methodology we propose is generally applicable to the characterization and comparison of network–level social structures across multiple settings, such as different organizations, communities, or social groups, and to the examination of sources of variability in network structure. We first fit a p^* model (Wasserman and Pattison 1996) to each network to obtain estimates for effects of six structural properties on the probability of the graph. We then calculate predicted tie probabilities for each network, using both its own parameter estimates and the estimates from every other network in the collection. Comparison is based on the similarity between sets of predicted tie probabilities. We then use correspondence analysis to represent the similarities among all 42 networks and interpret the resulting configuration using information about the species and relations involved. Results show that similarities among the networks are due more to the kind of relation than to the kind of animal.     

Processes of Knowledge Production in Social Movements as Multi‐level Power Dynamics

Most literature related to the study of processes of knowledge production within social movements neglects how power relations between participants rooted on structural inequalities shape such processes. It also underestimates how such inequalities and the very dynamics of movements intersect in the setting up of the ‘boundaries’ of ‘insidership’ and ‘outsidership’, as well as of the terms implicit in different forms of participation. This article makes a review of theoretical and methodological literature that is relevant to the study of processes of knowledge production within social movements. Based on that review, it proposes the concept of ‘multi‐level power dynamics’ as a tool for future research on the way in which such processes are shaped by power relations between movement members endowed with, or experiencing a differentiated access to different forms of knowledge, as well as with actors within the state and networks promoting the diffusion of ideas and strategies.     

Chinese Migrants' Class Mobility in Hong Kong

Resources such as education and social networks are likely to contribute to migrants' upward mobility in the class hierarchy. Moreover, according to structural fit theory, the contribution tends to be contingent on age and social network size. The contingency is the major concern of the present study of mainland Chinese migrants in Hong Kong, which is somewhat different from the Chinese mainland economically, politically and even culturally. In this study, we show that the conditions for upward mobility are some human and social resources and their various combinations. Notably, schooling after arrival in Hong Kong contributed more to the upward mobility of the migrant who was younger or had a larger social network at the time of arrival in Hong Kong. Purportedly, promoting the migrant's integration with the school and local social network would prepare the migrant for upward mobility.     

The Analysis of Duocentric Social Networks: A Primer

Marriages and other intimate partnerships are facilitated or constrained by the social networks within which they are embedded. To date, methods used to assess the social networks of couples have been limited to global ratings of social network characteristics or network data collected from each partner separately. In the current article, the authors offer new tools for expanding on the existing literature by describing methods of collecting and analyzing duocentric social networks, that is, the combined social networks of couples. They provide an overview of the key considerations for measuring duocentric networks, such as how and why to combine separate network interviews with partners into one shared duocentric network, the number of network members to assess, and the implications of different network operationalizations. They illustrate these considerations with analyses of social network data collected from 57 low‐income married couples, presenting visualizations and quantitative measures of network composition and structure.     

Chronic illness and social network bridging in later life

Chronic disease has profound impacts on the structural features of individuals’ interpersonal connections such as bridging — ties to people who are otherwise poorly connected to each other. Prior research has documented competing arguments regarding the benefits of network bridging, but less is known about how chronic illness influences bridging and its underlying mechanisms. Using data on 1555 older adults from the National Social Life, Health, and Aging Project (NSHAP), I find that older adults diagnosed with chronic illness tend to have lower bridging potential in their networks, particularly between kin and non-kin members. They also report more frequent interactions with close ties but fewer neighbors, friends, and colleagues in their networks, which mediates the association between chronic illness and social network bridging. These findings illuminate both direct and indirect pathways through which chronic illness affects network bridging and highlight the context-specific implications for social networks in later life.     

A Nash bargaining model for simple exchange networks

Starting from exogenously given negotiation networks, sociological exchange theories explain bilateral divisions of fixed surpluses (e.g., cake, dollar) as consequences of the partners’ structural embeddedness. In accordance with the available experimental evidence, we focus on simple exchange networks and present a formal model for predicting profit splits from such structures. In contrast to other approaches, we combine the generalized Nash bargaining solution from game theory with the assumption that both relational features and network positions affect exchange outcomes. The resulting point predictions for profit splits correspond closely with experimental results obtained by Cook et al. [Cook, K.S., Emerson, R.M., Gillmore, M.R., Yamagishi, T., 1983. The distribution of power in exchange networks: theory and experimental results. American Journal of Sociology 89, 275–305], Lovaglia et al. [Lovaglia, M.J., Skvoretz, J., Willer, D., Markovsky, B., 1995. Negotiated exchanges in social networks. Social Forces 74, 123–155], Markovsky et al. [Markovsky, B., Willer, D., Patton, T., 1988. Power relations in exchange networks. American Sociological Review 53, 220–236], Simpson and Willer [Simpson, B., Willer, D., 1999. A new method for finding power structures. In: Willer, D. (Ed.), Network Exchange Theory. Praeger, Westport, CT, pp. 270–284], Skvoretz and Fararo [Skvoretz, J., Fararo, T.J., 1992. Power and network exchange: an essay toward theoretical unification. Social Networks 14, 325–344], Skvoretz and Willer [Skvoretz, J., Willer, D., 1993. Exclusion and power: a test of four theories of power in exchange networks. American Sociological Review 58, 801–818] as well as Yamagishi et al. [Yamagishi, T., Gillmore, M.R., Cook, K.S., 1988. Network connections and the distribution of power in exchange networks. American Journal of Sociology 93, 833–851].