rss_2.0Journal of Social Structure FeedSciendo RSS Feed for Journal of Social Structure of Social Structure 's Cover Network Analysis Network Analysis of Twitter's Crackdown on the QAnon Conversation<abstract> <title style='display:none'>Abstract</title> <p>The QAnon conspiracy theory holds that former President Trump is fighting a ‘deep-state’ cabal of Satan-worshipping, cannibalistic pedophiles running a global child sex-trafficking ring. Conspirators include liberal Hollywood actors, Democratic politicians, financial elites, and even some religious leaders. Prominent politicians have embraced it, and the media increasingly covered it in the lead-up to the 2020 Presidential Election and beyond. Beginning on 4chan message boards in October 2017, QAnon narratives proliferated across popular social media platforms as individuals engaged in QAnon-related conversations on one platform shared links to ‘reputable’ content on others. In this paper, we draw on insights drawn from studies of diffusion and use social network analysis to analyze the networks generated by Twitter users from sharing external QAnon-related social media content via URLs during two key time frames: (1) the peak of QAnon Twitter activity in the Spring of 2020 and (2) the period following Twitter's crackdown on QAnon activities in July 2020. Our analysis reveals that the tweets and retweets of just a few actors accounted for most of the sharing of links to external social media sites, suggesting that other users saw them as reliable sources of information. It also shows that Twitter's crackdown impacted some aspects of the URL-sharing network. We conclude by briefly considering strategies for countering conspiracy theories and offering suggestions for future research.</p> </abstract>ARTICLE2022-05-16T00:00:00.000+00:00Syndicate Women: Gender and Networks in Chicago Organized Crime a Clustering: An A Posteriori Method for Social Networks<abstract><title style='display:none'>Abstract</title><p>Selecting an appropriate method of clustering for network data a priori can be a frustrating and confusing process. To address the problem we build on an a posteriori approach developed by Grimmer and King (2011) that compares hundreds of possible clustering methods at once through concise and intuitive visualization. We adapt this general method to the context of social networks, extend it with additional visualization features designed to enhance interpretability, and describe its principled use, outlining steps for selecting a class of methods to compare, interpreting visual output, and making a final selection. The interactive method, implemented in R, is demonstrated using Zachary’s karate club, a canonical dataset from the network literature.</p></abstract>ARTICLE2019-08-14T00:00:00.000+00:00Networks and Religion: Ties that Bind, Loose, Build Up, and Tear Down<abstract><title style='display:none'>Abstract</title><p>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.</p></abstract>ARTICLE2019-08-13T00:00:00.000+00:00Castells’ network concept and its connections to social, economic and political network analyses<abstract><title style='display:none'>Abstract</title><p>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, <italic>The Information Age</italic> 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.</p></abstract>ARTICLE2019-08-13T00:00:00.000+00:00A Multigraph Approach to Social Network Analysis<abstract><title style='display:none'>Abstract</title><p>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.</p></abstract>ARTICLE2019-08-13T00:00:00.000+00:00External Threat as Coercion<abstract><title style='display:none'>Abstract</title><p>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.</p></abstract>ARTICLE2019-08-13T00:00:00.000+00:00Using to Teach Social Networks<abstract><title style='display:none'>Abstract</title><p><italic>Lord of the Flies</italic> 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.</p><p>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.</p></abstract>ARTICLE2019-08-13T00:00:00.000+00:00A Longitudinal Analysis of Gendered Association Patterns: Homophily and Social Distance in the General Social Survey<abstract><title style='display:none'>Abstract</title><p>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.</p></abstract>ARTICLE2019-08-13T00:00:00.000+00:00Structural Balance and Signed International Relations<abstract><title style='display:none'>Abstract</title><p>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.</p></abstract>ARTICLE2019-08-13T00:00:00.000+00:00Structural Cohesion: Visualization and Heuristics for Fast Computation<abstract><title style='display:none'>Abstract</title><p>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.</p></abstract>ARTICLE2019-08-13T00:00:00.000+00:00Understanding the Influential People and Social Structures Shaping Compliance<abstract><title style='display:none'>Abstract</title><p>This study integrated efforts to identify influential people and to extend theories of structural predictors of compliance. Adults (<italic>N</italic> = 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.</p></abstract>ARTICLE2019-08-13T00:00:00.000+00:00U.S. and Whom? Structures and Communities of International Economic Research<abstract><title style='display:none'>Abstract</title><p>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.</p></abstract>ARTICLE2019-08-13T00:00:00.000+00:00Sender- and receiver-specific blockmodels<abstract><title style='display:none'>Abstract</title><p>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 ≤ <italic>i</italic> ≤ c, 1 ≤ <italic>v</italic> ≤ n, where í specifies the group membership of a sending vertex and <italic>ν</italic> specifies the identity of the receiving vertex. In addition, group membership is consider to be random, with parameters (í&gt;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 (≠<sub>u</sub>j) for 1 ≤ <italic>u</italic> ≤ n, <italic>1 &lt; j &lt; c</italic> depend on the membership of a vertex receiving a directed edge. We apply both models to several sets of social network data.</p></abstract>ARTICLE2019-08-13T00:00:00.000+00:00Hierarchy in Mixed Relation Networks: Warfare Advantage and Resource Distribution in Simulated World-Systems<abstract><title style='display:none'>Abstract</title><p>Building on world-systems theory, simulation models of 5-line intersocietal networks were generated in an effort to understand systemic power hierarchies. The societal nodes were exclusively connected by three types of interaction: migration, warfare, and unequal trade. These networks can be considered “mixed relation” networks due to the ways in which these types of ties combine positive and negative sanction flows. Insights from elementary theory were employed to understand how exclusion from these different types of ties might influence the resulting power distributions. Additionally, the resource carrying capacity of the nodes was varied by structural position in an effort to differentiate the influence of structural position and individual attributes on location in the hierarchy. It was determined that exclusion from interaction is likely a structural, scale invariant mechanism that helps to determine power distributions above and beyond the inherent attributes of network actors.</p></abstract>ARTICLE2019-08-14T00:00:00.000+00:00A Family of Affiliation Indices for Two-Mode Networks<abstract><title style='display:none'>Abstract</title><p>An affiliation network consists of actors and events. Actors are affiliated with each other by virtue of the events they mutually attend. This article introduces a family of affiliation measures that captures the extent of actors’ affiliations in the network. At one extreme, one might have an actor who attended many events, but none of these events were attended by any of the other actors in the network. Although of high degree, in no reasonable interpretation would such an actor be considered highly affiliated with other actors in the network. At the other extreme, one might have an actor defined by a collection of events, all of which were attended by another actor(s), making the actor as enmeshed in the network as possible. Most actors will be between these extremes, with some events being shared by varying others, and some not. This article introduces a family of affiliation measures based on the entries of the co-occurrence matrix. After defining the measures, the cumulative distribution function of first-order affiliation is derived and expressed as a difference of binomials.</p></abstract>ARTICLE2019-08-14T00:00:00.000+00:00An Analysis of the ‘Failed States Index’ by Partial Order Methodology<abstract><title style='display:none'>Abstract</title><p>Often objects are to be ranked. However, there is no measurable quantity available to express the ranking aim and to quantify it. The consequence is that indicators are selected, serving as proxies for the ranking aim. Although this set of indicators is of great importance for its own right, the most commonly used practice to obtain a ranking is an aggregation method. Any aggregation, however suffers from the effect of compensation, because the aggregation technique is in the broadest sense an averaging method. Here an alternative is suggested which avoids this averaging and which is derived from simple elements of the theory of partially ordered sets (posets). The central concept in partial order is the ‘concept of comparison’ and the most general outcome is a web of relations between objects according to their indicator values, respecting the ranking aim.</p><p>As an example the ‘Failed State Index’ (FSI), annually prepared by the Fund of Peace is selected. The FSI is based on twelve individual contextual different indicators, subsequently transformed into a single composite indicator, by simple addition of the single indicator values. Such an operation leaves space for compensation effects, where one or more indicators level out the effect of others. Hence, a comparison between the single states (in total 177) based on their mutual FSI ranking has its limitations as the comparisons are made based on the composite indicator. We show that brain drain is one of the indicators in the FSI-study that plays a crucial role in the ranking, whereby the ranking aim is the stabilization of nations.</p></abstract>ARTICLE2019-08-14T00:00:00.000+00:00Using Visualizations to Explore Network Dynamics<abstract><title style='display:none'>Abstract</title><p>Network analysis has become a popular tool to examine data from online social networks to politics to ecological systems. As more computing power has become available, new technology-driven methods and tools are being developed that can support larger and richer network data, including dynamic network analysis. This timely merger of abundant data and cutting edge techniques affords researchers the ability to better understand networks over time, accurately show how they evolve, find patterns of growth, or study models such as the diffusion of innovation. We combine traditional methods in social network analysis with new innovative visualizations and methods in dynamic network studies to explore an online tobacco-control community called GLOBALink, using almost twenty years of longitudinal data. We describe the methods used for the study, and perform an exploratory network study that links empirical results to real-world events.</p></abstract>ARTICLE2019-08-14T00:00:00.000+00:00If Parsons had Pajek: The Relevance of Midcentury Structural-Functionalism to Dynamic Network Analysis<abstract><title style='display:none'>Abstract</title><p>Social network analysis has been one of the most influential scientific revolutions of the past century. Its success has been due, in part, to its methodological sophistication and the emphasis it places on identifying and clearly depicting features of social structure. As such, social network analysis is often viewed in stark contrast to the structuralist paradigm that dominated the social sciences prior to its rise – structural–functionalism - in the mid-20th century. In this paper, we highlight important connections that exist between the key assumptions of social network analysis and the key tenets of some of the most influential structural-functional theories – especially those of Robert K. Merton and Talcott Parsons and their collaborators and followers. We reveal a substantial affinity between some of their most influential ideas and contemporary analysis of social network <italic>dynamics</italic>, in particular, and several ways in which their work could inform promising advances in this line of research. Our ultimate goal is to highlight the prospect of using these theories to guide future analyses of the dynamics of large social systems and the sequences of real-time action that compose them.</p></abstract>ARTICLE2019-08-13T00:00:00.000+00:00en-us-1