Tom 16 (2015): Zeszyt 1 (January 2015)

Multigraphs are graphs where multiple edges and edge loops are permitted. The main purpose of this article is to show the versatility of a multigraph approach when analysing social networks. Multigraph data structures are described and it is exemplified how they naturally occur in many contexts but also how they can be constructed by different kinds of aggregation in graphs. Special attention is given to a random multigraph model based on independent edge assignments to sites of vertex pairs and some useful measures of the local and global structure under this model are presented. Further, it is shown how some general measures of simplicity and complexity of multigraphs are easily handled under the presented model.

We use balance theoretic ideas to study the dynamics of the international system of nations in a network of signed relations from 1946 through 1999. Using the Correlates of War data for this period, we apply pre-specified signed blockmodeling to characterize the fundamental structure of this network. Even though the system expanded greatly with many ties being created and/or destroyed, the basic structure remained the same but with new positions being added over time. The blockmodels generated temporal measures of imbalance, as did the counts of imbalanced triples. Regardless of using the line index of imbalance or the number of imbalanced 3-cycles, the results provided decisive evidence contradicting the balance theoretic hypothesis of signed networks moving towards balanced states. Structural balance theory remains very useful by pointing to the more important study of how and why signed networks move towards and away from balance at different points over time. Some major methodological problems for studying signed networks, regardless of whether they involve nations or human actors, were raised and addressed. Proposals for future research are suggested for modeling and understanding the dynamics of signed networks.

How has the passage of time impacted the ego networks of males and females? I compare the homophily and social distances of males and females using the 1985 and 2004 GSS networks modules. The results indicate that change has been gradual and incremental rather than radical. In 2004 less social distance separates associates for women than for men, and males differentiate more among levels of education. The results suggest that macro-level structural changes have not been sufficient to produce similarly large changes in ego network composition.

This study integrated efforts to identify influential people and to extend theories of structural predictors of compliance. Adults (N = 195) were shown a sociogram of 11 people who were connected by friendships. Participants were asked to imagine themselves in this group, identify a position for themselves, select another member for an interaction, and predict their likelihood of complying with the member’s request. Connectors (those wanting to link others) identified with more central positions for themselves and selected more central interaction partners. Agents with greater persuasive impact were more successful in gaining compliance from participants; for connectors, targets’ supportive impact also reduced their likelihood of compliance. Findings have implications for diffusion efforts that depend on interpersonal compliance, and for theories of social influence.

We propose a sender-specific blockmodel for network data which utilizes both the group membership and the identities of the vertices. This is accomplished by introducing the edge probabilities (ŵ¿,ν) for 1 ≤ i ≤ c, 1 ≤ v ≤ n, where í specifies the group membership of a sending vertex and ν specifies the identity of the receiving vertex. In addition, group membership is consider to be random, with parameters (í>í)í=io We present methods based on the EM algorithm for the parameter estimations and discuss the recovery of latent group memberships. A companion model, the receiver-specific blockmodel, is also introduced in which the edge probabilities (≠_uj) for 1 ≤ u ≤ n, 1 < j < c depend on the membership of a vertex receiving a directed edge. We apply both models to several sets of social network data.

In coercive relations, threats of negative sanctions extract valued positive sanctions from coercees. Only when coercion is direct, however, are the negative sanctions controlled by the coercer who benefits from the threats. Not previously investigated, indirect coercion relies on threats and negative sanctions that are external to the exploitative relation. We suggest that indirect coercion is ubiquitous. From their inception states have used the threat of external enemies to justify rulers’ increased powers and to provide a patina of legitimacy while, on a smaller scale, criminal organizations such as the mafia have long profited from offering protection. The purpose of this paper is to theoretically model and experimentally investigate indirect coercion and compare its effectiveness in extracting valued resources to that of direct coercion. Previous research has shown that all power structures, whether exchange, conflict or coercive, take two distinct forms, strong and weak. Therefore, experiments on strong and weak indirect coercion are run and are compared to new and previous experiments on strong and weak direct coercion. Theoretically grounded predictions are derived and tested for those structures.

Lord of the Flies is commonly assigned reading for high school and college students. The novel about shipwrecked boys is often analyzed thematically to examine how the boys’ perceived isolation on the island effects their attitudes and behavior. However, what is similarly apparent is that the society they develop while on the island establishes certain patterns, and is governed by collective rules (some more explicit than others). Here I demonstrate how those behavioral patterns and norms are useful for interpreting the concepts and analytic tools found in social network literature. I describe how I used the novel as a “capstone” project in four sections of an undergraduate Social Networks course. This demonstrates how students’ readings of the text revealed several common families of social network measures leveraged in the book’s plot.

I would like to thank Ryan Light, David Schaefer and Skye Bender-deMoll for helpful comments in preparing this manuscript. Any errors that remain are my own.

The structural cohesion model is a powerful theoretical conception of cohesion in social groups, but its diffusion in empirical literature has been hampered by operationalization and computational problems. In this paper, we start from the classic definition of structural cohesion as the minimum number of actors who need to be removed in a network in order to disconnect it, and extend it by using average node connectivity as a finer grained measure of cohesion. We present useful heuristics for computing structural cohesion that allow a speed-up of one order of magnitude over the algorithms currently available. We analyze three large collaboration networks (co-maintenance of Debian packages, co-authorship in Nuclear Theory and High-Energy Theory) and show how our approach can help researchers measure structural cohesion in relatively large networks. We also introduce a novel graphical representation of the structural cohesion analysis to quickly spot differences across networks.

Most studies concerned with empirical social networks are conducted on the level of individuals. The interaction of scientists is an especially popular research area, with the growing importance of international collaboration as a common sense result. To analyze patterns of cooperation across nations, this paper investigates the structure and evolution of cross-country co-authorships for the field of economics from 1985 to 2011. For a long time economic research has been strongly US centered, while influencing real-world politics all over the globe. We investigate the impact of the general trend of increasing international collaboration on the hegemonic structures in the “global department of economics.” A dynamic map of economic research is derived and reveals communities that are hierarchical and structured along the lines of external social forces, i.e. historical and political dimensions. Based on these findings, we discuss the influence of the core-periphery structure on the production of economic knowledge and the dissemination of new ideas.

That social networks play a central role in religious life is well accepted by most social scientists. We are reasonably confident, for instance, that they are crucial for the recruitment and retention of members, the diffusion of religious ideas and practices, motivating individuals to volunteer and become politically active, the health and well-being of people of faith, and conflict, radicalization, and (sometimes) violence. However, in conference presentations, journal articles, and books social network analysts have shown little interest in exploring the interplay of networks and religion. In this paper, I review, and in some cases expand upon, what social scientists of religion have learned about networks and religion. I conclude with a call for social network analysts to focus the analytical tools of social network analysis on a phenomenon that has and continues to exert considerable influence in today’s world.

This article discusses the conceptualization of network in Manuel Castells’ theory of network society and its relation to network analysis. Networks assumed a significant role in Castells’ opus magnum, The Information Age trilogy, in the latter half of the 1990s. He became possibly the most prominent figure globally in adopting network terminology in social theory, but at the same time he made hardly any empirical or methodological contribution to network analysis. This article sheds light on this issue by analyzing how the network logic embraced by Castells defines the social, economic, and political relations in his theory of network society, and how such aspects of his theory relate to social network analysis. It is shown that Castells’ institutional network concept is derived from the increased relevance of networks as the emerging form of social organization, epitomized by the idea of global networks of instrumental exchanges. He did not shed light on the internal dynamics of networks, but was nevertheless able to use network as a powerful metaphor that aptly portrayed his idea of the new social morphology of informational capitalism.