<abstract>
<title style='display:none'>Abstract</title>
<italic><bold>Background and objective</bold></italic>. Nutrition information conveyed by popular entities through online social networking sites (i.e., social media influencers) has the potential to impact consumer eating behavior through mechanisms of social influence. Little is known about how online communities of food-related social media influencers are structured, which could reveal influencers’ opportunities to observe and spread nutrition-related content and information design practices. This study explored patterns of social relationships (social capital, conservation of resources, and homophily) within a network of prominent food bloggers on Twitter (<italic>N</italic> = 44). <italic><bold>Methods</bold></italic>. Data on Twitter following/follower relationships and Twitter use (number of tweets, favorited tweets) were collected from bloggers’ Twitter profiles. Bloggers represented eight topical subcategories of food blogs (e.g., family cooking, cocktails) and comprised a one-mode social network with directed ties indicating Twitter following/follower relationships. Structural evidence of patterns of social relationships was investigated through social network visualization, centrality measures (in-degree/out-degree centrality, density, reciprocity), and inferential tests. <italic><bold>Results</bold></italic>. The overall network density of directed ties was 21%, with wide variability in individual blogger centrality across multiple measures. Cocktails, cooking, special diets, and culinary travel bloggers had more dense ties to bloggers in their own subcategories. Within the network, favorited tweets and outreach (Twitter following relationships) were positively associated with popularity (Twitter follower relationships). <italic><bold>Conclusions</bold></italic>. Food bloggers in this study formed a partially connected network, supporting the conservation of resources framework. Homophily was evident in some, but not all, topical subcategories. Associations among Twitter use, outreach, and popularity generally supported the social capital framework. Future studies should explore influencers’ motivations for connecting on social networking sites, and how content and information design practices spread among influencers.
</abstract>

Exploring Patterns of Social Relationships among Food Bloggers on Twitter Using a Social Network Analysis Approach

<abstract><title style='display:none'>Abstract</title>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.</abstract>

Structural Balance and Signed International Relations

<abstract><title style='display:none'>Abstract</title>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.</abstract>

Castells’ network concept and its connections to social, economic and political network analyses

<abstract><title style='display:none'>Abstract</title>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.</abstract>

A Longitudinal Analysis of Gendered Association Patterns: Homophily and Social Distance in the General Social Survey

<abstract><title style='display:none'>Abstract</title>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.</abstract>

If Parsons had Pajek: The Relevance of Midcentury Structural-Functionalism to Dynamic Network Analysis*

Book Review: <italic>The Oxford Handbook of Social Networks</italic>

<abstract>
<title style='display:none'>Abstract</title>
Centrality measures are widely utilized in complex networks to assess the importance of nodes. The choice of measure depends on the network type, leading to diverse node rankings. This paper aims to compare various centrality measures by examining their correlations. We specifically focus on the Pearson correlation coefficient and Spearman correlation. Pearson correlation considers node centrality values, while Spearman correlation is based on node ranks. Our study encompasses different network topologies, including random, scale-free, and small-world networks. We investigate how these network structures influence correlation values. The main part of the paper describes the relationship between correlations and network model parameters. Additionally, we explore the impact of global network characteristics on correlations, as well as their direct connection to network parameters. Through a systematic review of literature-based centrality measures, we have identified and selected the most commonly employed ones to investigate their correlation including degree centrality, betweenness centrality, eigenvector centrality, and closeness centrality. Our findings reveal that correlations in random networks are minimally affected by network structure, whereas restructuring significantly impacts correlations in other networks. In particular, we show a notable impact of structural parameter variations on correlations within small-world networks. Furthermore, we demonstrate the substantial influence of fundamental network characteristics such as spectral gap, global efficiency, and majorization gap on correlations. We show that amongst the various properties, the spectral gap stands out as the most valuable indicator for estimating correlations.
</abstract>

An Analysis of Correlation and Comparisons Between Centrality Measures in Network Models

Longitudinal Network Models

A Research Agenda for Social Networks and Social Resilience

Personal Networks: Classic Readings and New Directions in Egocentric Analysis

Trade and Nation: How Companies and Politics Reshaped Economic Thought

Living in Networks: The Dynamics of Social Relations

<abstract><title style='display:none'>Abstract</title>Changes in observed social networks may signal an underlying change within an organization, and may even predict significant events or behaviors. The breakdown of a team’s effectiveness, the emergence of informal leaders, or the preparation of an attack by a clandestine network may all be associated with changes in the patterns of interactions between group members. The ability to systematically, statistically, effectively and efficiently detect these changes has the potential to enable the anticipation, early warning, and faster response to both positive and negative organizational activities. By applying statistical process control techniques to social networks we can rapidly detect changes in these networks. Herein we describe this methodology and then illustrate it using four data sets, of which the first is the Newcomb fraternity data, the second set of data is collected on a group of mid-career U.S. Army officers in a week long training exercise, the third is the perceived connections among members of al Qaeda based on open source, and the fourth data set is simulated using multi-agent simulation. The results indicate that this approach is able to detect change even with the high levels of uncertainty inherent in these data.</abstract>

Detecting Change in Longitudinal Social Networks

<abstract><title style='display:none'>Abstract</title>Our goal in this paper is to explore two generic approaches to disrupting dark networks: kinetic and non-kinetic. The kinetic approach involves aggressive and offensive measures to eliminate or capture network members and their supporters, while the non-kinetic approach involves the use of subtle, non-coercive means for combating dark networks. Two strategies derive from the kinetic approach: Targeting and Capacity-building. Four strategies derive from the non-kinetic approach: Institution-Building, Psychological Operations, Information Operations and Rehabilitation. We use network data from Noordin Top’s South East Asian terror network to illustrate how both kinetic and non-kinetic strategies could be pursued depending on a commander’s intent. Using this strategic framework as a backdrop, we strongly advise the use of SNA metrics in developing alterative counter-terrorism strategies that are contextdependent rather than letting SNA metrics define and drive a particular strategy.</abstract>

Strategies for Combating Dark Networks

<abstract><title style='display:none'>Abstract</title>In this paper, we employ archival materials from multiple institutional sources to reconstruct the dynamic network of interorganizational collaboration that emerged in response to the Hurricane Katrina disaster of late 2005. Over the period from initial storm formation through the first week following landfall in Louisiana, we record active participation by over 1,500 organizations in response activities. We here conduct an exploratory analysis of the growth and evolution of the network of collaboration among responding organizations, an identification of organizations that emerged as central actors in the response process, and the cohesive subgroups that crystallized within the larger network. Finally, we conclude with a discussion of several issues related to the use of archival methods in research on interorganizational networks in disaster settings, and to the use of automated methods for network extraction.</abstract>

Interorganizational Collaboration in the Hurricane Katrina Response*

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Journal of Social Structure

The Journal of Social Structure (JoSS) is an electronic journal of the International Network for Social Network Analysis (INSNA). It is designed...

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The Journal of Social Structure (JoSS) is an electronic journal of the International Network for Social...