Tweeting #RamNavami: A Comparison of Approaches to Analyzing Bipartite Networks

Bipartite networks, also known as two-mode networks or affiliation networks, are a class of networks in which actors or objects are partitioned into two sets, with interactions taking place across but not within sets. These networks are omnipresent in society, encompassing phenomena such as student-teacher interactions, coalition structures and international treaty participation. With growing data availability and proliferation in statistical estimators and software, scholars have increasingly sought to understand the methods available to model the data-generating processes in these networks. This article compares three methods for doing so: (a) Logit (b) the bipartite Exponential Random Graph Model (ERGM) and (c) the Relational Event Model (REM). This comparison demonstrates the relevance of choices with respect to dependence structures, temporality, parameter specification and data structure. Considering the example of Ram Navami, a Hindu festival celebrating the birth of Lord Ram, the ego network of tweets using #RamNavami on 21April 2021 is examined. The results of the analysis illustrate that critical modelling choices make a difference in the estimated parameters and the conclusions to be drawn from them.

Shifting Coalitions within the Youth Climate Movement in the US

How has the youth climate movement in the US grown since the Climate Strikes began and in what ways did it change as it grew? This article takes advantage of a unique dataset that includes surveys from activists who organized the nationally coordinated climate strikes in the US that began with Fridays for Future in spring 2019. Building on the research on alliance building and strategic coalitions, this article analyzes how the patterns of participation changed over the period of the study. We employ social network analysis to map the affiliation networks among the organizers of these events to assess the coalitions of groups involved and the shifting organizational landscape. Our analysis does not provide evidence that groups spanned the boundaries across movements, nor does it show that identity plays a role in coalition building in this movement. Instead, by mapping out the coalition of organizations within this movement and how connections among them change over time, we see clear evidence that this youth-led movement was reoriented by adult-led organizations. Our article concludes by considering how these findings suggest the future trajectory of the youth climate movement and its role in a ‘new climate politics’ in America.

Shifting Coalitions within the Youth Climate Movement in the US

How has the youth climate movement in the US grown since the Climate Strikes began and in what ways did it change as it grew? This article takes advantage of a unique dataset that includes surveys from activists who organized the nationally coordinated climate strikes in the US that began with Fridays for Future in spring 2019. Building on the research on alliance building and strategic coalitions, this article analyzes how the patterns of participation changed over the period of the study. We employ social network analysis to map the affiliation networks among the organizers of these events to assess the coalitions of groups involved and the shifting organizational landscape. Our analysis does not provide evidence that groups spanned the boundaries across movements, nor does it show that identity played a role in coalition building in this movement. Instead, by mapping out the coalition of organizations within this movement and how connections among them change over time, we see clear evidence that this youth-led movement was reoriented by adult-led organizations. Our article concludes by considering how these findings suggest the future trajectory of the youth climate movement and its role in a ‘new climate politics’ in America.

The small world of German CEOs: a multi-method analysis of the affiliation network structure

This paper seeks to understand the structure of corporate networks in the period following the dissolution of Deutschland AG (“Germany Inc.”). For this purpose, affiliation networks among chief executive officers (CEOs) that are based on common membership in various societal organizations will be examined. I apply an innovative mix of methods for studying a sample of CEOs from the 100 top companies in Germany in the 2010s. Based on social network analysis, I show that the overall affiliation network has all features of a small-world network, i.e., a high clustering coefficient and a short path length among the CEOs. The average degree of separation among German CEOs is only two steps. Another innovative contribution of this paper is its study of the linkage between affiliation network features and patterns of corporate recruitment. Using multiple correspondence analysis, I show that different subgroups of the overall affiliation network have their specific network characteristics and recruitment patterns. Within the network, managers from automotive and technical engineering often assume brokerage positions, while managers from the trade branch are largely isolated. This study shows that the affiliation networks and corporate recruitment patterns are interlinked; the transformation of corporate networks is a dynamic outcome of interrelations among different subgroups within the network, each with distinct educational, professional, and network characteristics.

How College Makes Liberals (or Conservatives)

The author examines the role of affiliation networks in shaping the political identities of students in college, using panel survey data from a case study of a predominantly liberal institution, tracking students’ political identities and affiliation memberships throughout the course of college. Although there was some self-selection into politically homophilous student organizations and majors, the extent of political sorting was relatively low, which resulted in considerable political heterogeneity in the affiliation networks. During the course of college, students’ political identities shifted in both liberal and conservative directions. Results from hierarchical multinomial logistic regressions suggest that identity transitions were driven by both the political composition of peer networks and influences outside the educational institution, such as family and prior socialization. This research underscores the importance of considering network stratification and individual contexts for understanding heterogeneous influences of seemingly uniform institutional settings.