Centrality in social networks: ii. experimental results

Three competing hypotheses about structural centrality are explored by means of a replication of the early MIT experiments on communication structure and group problem-solving. It is shown that although two of the three kinds of measures of centrality have a demonstrable effect on individual responses and group processes, the classic measure of centrality based on distance is unrelated to any experimental variable. A suggestion is made that the positive results provided by distance-based centrality in earlier experiments is an artifact of the particular structures chosen for experimentation.     

Crowdfunding digital platforms: Backer networks and their impact on project outcomes

Crowdfunding platforms serve to connect project creators and backers. Previous research has explored several project and platform determinants that impact crowdfunding outcomes. However, there has been limited research on these determinants at an individual level. Our paper addresses how backers may influence the outcomes of projects in crowdfunding platforms. We explore several methods commonly used in the industry to identify influence and show that centrality measures through a backer affiliation network best exemplifies influence. Using data from Kickstarter, we construct a weighted backer network based on 52,678 common projects backed by 11,134 backers. Controlling for digital media mentions and project quality, we find evidence that backers in central positions within the network have a positive impact on multiple project outcomes such as the project success rates, amount of funds raised, speed of reaching the crowdfunding goal as well as the number of backers contributing to the project. These findings are replicated and reinforced by using data from a different crowdfunding platform using the entire backer network based on 1095 projects backed by 87,896 backers. Several robustness tests are used to validate these results.     

Ranking terrorists in networks: A sensitivity analysis of Al Qaeda's 9/11 attack

All over the world, intelligence services are collecting data concerning possible terrorist threats. This information is usually transformed into network structures in which the nodes represent the individuals in the data set and the links possible connections between these individuals. Unfortunately, it is nearly impossible to keep track of all individuals in the resulting complex network. Therefore, Lindelauf et al. (2013) introduced a methodology that ranks terrorists in a network. The rankings that result from this methodology can be used as a decision support system to efficiently allocate the scarce surveillance means of intelligence agencies. Moreover, usage of these rankings can improve the quality of surveillance which can in turn lead to prevention of attacks or destabilization of the networks under surveillance.The methodology introduced by Lindelauf et al. (2013) is based on a game theoretic centrality measure, which is innovative in the sense that it takes into account not only the structure of the network but also individual and coalitional characteristics of the members of the network. In this paper we elaborate on this methodology by introducing a new game theoretic centrality measure that better takes into account the operational strength of connected subnetworks.Moreover, we perform a sensitivity analysis on the rankings derived from this new centrality measure for the case of Al Qaeda's 9/11 attack. In this sensitivity analysis we consider firstly the possible additional information available about members of the network, secondly, variations in relational strength and, finally, the absence or presence of a small percentage of links in the network. We also introduce a case specific method to compare the different rankings that result from the sensitivity analysis and show that the new centrality measure is robust to small changes in the data.     

Collegial oligarchy and networks of normative alignments in transnational institution building

This paper presents a combined relational and cultural approach to transnational institution building by focusing on a network analysis of a small collegial oligarchy and normative alignments among its peers. To contribute to a theory of institutionalization, we propose hypotheses about whom professionals as institutional entrepreneurs are likely to select as members of their collegial oligarchy, about the role of social networks among them in identifying these leaders, and about the costs of alignments on these leaders’ normative choices. We test these hypotheses using mainly Exponential Random Graph Models (ERGMs) applied to a dataset including network information and normative choices collected at the so-called Venice Forum – a field-configuring event that was central in creating and mobilizing a network of European patent judges for the construction of a new transnational institution, the European Unified Patent Court. We track normative alignments on the collegial hierarchy in this network of judges and their divergent interpretations of the contemporary European patent. Highlighting this under-examined articulation of relational infrastructures and cultural framing in transnational institutionalization shows how Northern European forms of capitalism tend to dominate in this institutionalization process at the expense of the Southern European forms. It also helps reflect on the usefulness of analyses of small networks of powerful players in organizational societies, where power and influence are highly concentrated.     

Gender,rank, and social networks on an enterprise social media platform

In this paper, we harness server-side data—540,000 messages generated by 2085 users on TamTamy, an Enterprise Social Media (ESM) platform—to examine how gender and rank shaped “homophily” (the tendency to connect with similar others) and centrality in an ESM network. Drawing on the logic of “distinctiveness theory,” which argues that the numeric rarity of a category in a given setting promotes the use of that category as a basis for connecting with others, we hypothesized and found: (a) the tendency to connect with same-gender others was stronger among women than among men; (b) the tendency to connect with same-rank others was stronger among high-ranking employees than among low-ranking employees; (c) for high-ranking men, rank was more important than gender as a basis for connecting with others; and (d) for low-ranking women, gender was more important than rank as a basis for connecting with others. We also found that whereas higher ranking individuals were more likely to be in central (bridging) positions in the overall network, gender was unrelated to network centrality. Our study suggests that the affordances of ESM for open and distributed communications notwithstanding, the social networks that emerge on ESM platforms may reinforce social stratification on some dimensions while diminishing it on others.     

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.     

Rethinking the dynamic of global production networks: Integrate the influence of suppliers and towards a flexible strategy making causal mechanism

The global production network (GPN) 2.0 framework mainly considers the organizational capabilities of lead firms, neglecting the influence of supplier capabilities on the strategic making of lead firms. I argue that the GPN 2.0 framework must integrate the influence of supplier capabilities (both industrial and individual firm levels) to better explain the organization of the global economy. Industrial-level capability determines the possible strategic choices that firms may make under certain dynamic combinations, whereas the individual firm level determines the geographic extension direction of GPNs. Therefore, this study incorporates the influence of suppliers and builds a more flexible strategy-making causal mechanism other than the definitive and limiting causal mechanism in GPN 2.0. I hope this article can promote the further development of GPN 2.0 and convey some valuable concepts to make it perform better in deconstructing the organization of the global economy in the real world.     

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 New Model for Information Diffusion in Heterogeneous Social Networks

This paper discusses a new model for the diffusion of information through heterogeneous social networks. In earlier models, when information was given by one actor to another the transmitter did not retain the information. The new model is an improvement on earlier ones because it allows a transmitter of information to retain that information after telling it to somebody else. Consequently, the new model allows more actors to have information during the information diffusion process. The model provides predictions of diffusion times in a given network at the global, dyadic, and individual levels. This leads to straightforward generalizations of network measures, such as closeness centrality and betweenness centrality, for research problems that focus on the efficiency of information transfer in a network. We analyze in detail how information diffusion times and centrality measures depend on a series of network measures, such as degrees and bridges. One important finding is that predictions about the time actors need to spread information in the network differ considerably between the new and old models, while the predictions about the time needed to receive information hardly differ. Finally, some cautionary remarks are made about using the model in empirical research.     

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.     

Universal evolution patterns of degree assortativity in social networks

Degree assortativity characterizes the propensity for large-degree nodes to connect to other large-degree nodes and low-degree to low-degree. It is important to describe the forces forming the network and to predict the behavior of dynamic systems on the network. To understand the evolutionary dynamics of degree assortativity, we collect a variety of empirical temporal social networks, and find that there is a universal pattern that the degree assortativity increases at the beginning of evolution and then decreases to a long-lasting stable level. We develop a bidirectional selection model to re-construct the evolution dynamic. In our model, we assume each individual has a social status that—in analogy to Pareto’s wealth distribution —follows a power-law distribution. We assume the social status determines the probability of an interaction between two actors. By varying the ratio of link establishment from within the same status level to across different status levels, the simulated network can be tuned to be assortative or disassortative. This suggests that the rise-and-fall pattern of degree assortativity is a consequence of the different network-forming forces active at different mixing of status. Our simulations indicate that Pareto social status distribution in the population may drive the social evolution in a way of self-optimization to promote the social interaction among individuals and the status gap plays an important role for the assortativity of the social network.     

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.     

Centrality in affiliation networks

This paper discusses the conceptualization, measurement, and interpretation of centrality in affiliation networks. Although centrality is a well-studied topic in social network analysis, and is one of the most widely used properties for studying affiliation networks, virtually all discussions of centrality and centralization have concerned themselves with one-mode networks. Bonacich's work on simultaneous group and individual centralities is a notable exception (Social Networks, 1991, 13, 155–168). I begin by outlining the distinctive features of affiliation networks and describe four motivations for centrality indices in affiliation networks. I then consider properties of some existing centrality indices for affiliation networks, including the relationship between centralities for actors and events in these networks, and present a new conceptualization of centrality that builds on the formal properties of affiliation networks and captures important theoretical insights about the positions of actors and events in these networks. These centralities are then illustrated on Galaskiewicz's data on club and board memberships of a sample of corporate executive officers (Social Organization of an Urban Grants Economy. New York: Academic Press, 1985). The conclusion to this paper discusses strengths and weaknesses of centrality indices when applied to affiliation networks.     

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.     

Who speaks up to whom? A relational approach to employee voice

We adopt a relational approach to examine the effects of social relations and formal structure on who speaks up to whom about problems at work. Data were collected in a two-wave employee survey in three Dutch preschools. Using exponential random graph modeling, we found significant positive effects of formal structure (recipient's hierarchical level; team co-membership) and good relations between speaker and recipient on the likelihood of voice in a dyad. Speaker's hierarchical level had positive effects, significant in Wave 1. Speaker's degree centrality significantly reduced the likelihood of voice, whereas recipient's degree centrality had no effect.     

Adolescent network positions and memory performance in adulthood: Evidence from sibling fixed effects models with sociometric network data

Although research has explored social factors influencing memory performance during adolescence, the impact of adolescent social network positions remains largely unknown. This study examines whether adolescent network position is associated with memory performance in adulthood, while also considering potential gender differences. The study used a sibling sample from the National Longitudinal Study of Adolescent to Adult Health (N = 2462) and employed sibling fixed effects models to account for unobserved family background factors, such as genetics, parental characteristics, family environment, and childhood neighborhood. Four dimensions of adolescent network position—i.e., popularity, sociality, degree centrality, and closeness centrality—were sociometrically assessed in schools. Memory performance in adulthood was measured using the Rey Auditory Verbal Learning Test. The sibling fixed effects estimates indicate that sociality, degree centrality, and closeness centrality are significantly associated with increased memory performance in adulthood, even after controlling for unobserved family heterogeneity as well as a set of individual-level covariates. In contrast, controlling for unobserved family heterogeneity attenuated the association for popularity, making it statistically insignificant. This study also provides evidence of gender differences in the association between social network position and memory performance. The associations for popularity, sociality, and degree centrality are more pronounced among men than women. This study’s findings highlight the importance of adolescent network positions as social determinants in shaping cognitive outcomes over the life course. Interventions that encourage positive peer interactions and reduce social isolation during adolescence may help improve cognitive health in the population.     

Informal lending networks in rural Ethiopia

Economic development in emergent nations is tied to smallholder subsistence populations whose livelihoods are vulnerable to exogenous shocks. When shocks occur, individuals often rely on resources embedded within informal insurance networks. Resource access is related to network position and reflected in properties such as centrality and reachability. We analyze a complete informal lending network (188 nodes, 295 ties) among the Sidama, an agro-pastoralist population in southwestern Ethiopia. Results indicate that culturally salient indicators of wealth, such as cattle ownership and gender, largely account for network structure. Analysis of a complete network further allows us to discuss the impact of global network properties, such as overall typology, on a communities response to different types of shocks (covariate and idiosyncratic). These findings extend our understanding of how individuals and communities engage informal lending networks in response to exogenous shocks.     

Embedding time in positions: Temporal measures of centrality for social network analysis

Digital data enable researchers to obtain fine-grained temporal information about social interactions. However, positional measures used in social network analysis (e.g., degree centrality, reachability, betweenness) are not well suited to these time-stamped interaction data because they ignore sequence and time of interactions. While new temporal measures have been developed, they consider time and sequence separately. Building on formal algebra, we propose three temporal equivalents to positional network measures that incorporate time and sequence. We demonstrate how these temporal equivalents can be applied to an empirical context and compare the results with their static counterparts. We show that, compared to their temporal counterparts, static measures applied to interaction networks obscure meaningful differences in the way in which individuals accumulate alters over time, conceal potential disconnections in the network by overestimating reachability, and bias the distribution of betweenness centrality, which can affect the identification of key individuals in the network.     

Social network structure and the trade-off between social utility and economic performance

We put forward a computational multi-agent model capturing the impact of social network structure on individuals’ social trust, willingness to cooperate, social utility and economic performance. Social network structure is modeled as four distinct social capital dimensions: degree, centrality, bridging and bonding social capital. Model setup draws from socio-economic theory and empirical findings based on our novel survey dataset. Results include aggregate-level comparative statics and individual-level correlations. We find, inter alia, that societies that either are better connected, exhibit a lower frequency of local cliques, or have a smaller share of family-based cliques, record relatively better aggregate economic performance. As long as family ties are sufficiently valuable, there is a trade-off between aggregate social utility and economic performance, and small world networks are then socially optimal. We also find that in dense networks and trustful societies, there is a trade-off between individual social utility and economic performance; otherwise both outcomes are positively correlated in the cross section.     

Where do intra-organizational advice relations come from? The role of informal status and social capital in social exchange

Social status and social capital frameworks are used to derive competing hypotheses about the emergence and structure of advice relations in organizations. Although both approaches build on a social exchange framework, they differ in their behavioral micro-foundations. From a status perspective, advice giving is a means to generate prestige, whereas asking advice decreases one's relative standing. At a structural level these motivations are expected to result in an overrepresentation of non-reciprocal dyads and non-cyclical triadic structures in the advice network, as well as in active advice seekers being unlikely to be approached for advice, especially by active advice givers. From a social capital perspective, advice seeking creates obligations for the advice seeker. At the structural level, this results in an overrepresentation of reciprocal dyads and cyclical triads, and active advice seekers to be unpopular as targets of advice seeking, especially for active advice givers. Analyses of four waves of a longitudinal sociometric study of 57 employees of a Dutch Housing Corporation provide partial support for both approaches. In line with the social capital perspective, we find reciprocal advice relations to be overrepresented at the dyad level. Results at the triad level support the social status arguments, according to which high status individuals will avoid asking advice from low status individuals. The implications for macro-structural properties of intra-organizational advice network are discussed.