Community Structure in Congressional Cosponsorship Networks

By Yan Zhang, Arthur J. Friend, Amanda L. Traud, M. A. Porter, James H. Fowler, Peter J. Mucha. 2007

186 citations recorded by the source corpus.

We study the United States Congress by constructing networks between Members of Congress based on the legislation that they cosponsor. Using the concept of modularity, we identify the community structure of Congressmen, who are connected via sponsorship/cosponsorship of the same legislation. This analysis yields an explicit and conceptually clear measure of political polarization, demonstrating a sharp increase in partisan polarization which preceded and then culminated in the 104th Congress (1995–1996), when Republicans took control of both chambers of Congress. Although polarization has since waned in the U.S. Senate, it remains at historically high levels in the House of Representatives.

Subfields: Communication, Political Science and International Relations, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/e1b3817f21474015807d2db1762d5d394437df42

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Citations in the corpus

Community detection in graphs (2009, methodology): “Porter and coworkers have carried out numerous studies on the subject (Porter et al., 2007, 2005; Zhang et al., 2008), by using data on the Congress of the United States.”
Social Structure of Facebook Networks (2011, unknown): “In addition to remarkable successes on benchmark problems, investigations of community structure have observed correspondence between communities and ‘‘ground truth’’ groups in diverse application areas—including the reconstruction of college football conferences [44] and the investigation of such s”
Communities in Networks (2009, methodology): “s. Advances in network science have also begun to uncover the ways in which social relationships shape political outcomes [34,35,92]. In this section, we describe our own work on legislative networks [91,92,113,120], in which community detection has played a central role. Consider a bipartite graph ”
Core-Periphery Structure in Networks (2012, methodology): “7 have been used previously to study Senators and Representatives in legislation cosponsorship networks [22, 23], which have in turn been compared to modularity-based measures of political partisanship that were studied using roll-call voting networks [71].”
Inferential Network Analysis with Exponential Random Graph Models (2011, background): “However, the majority of the cosponsorship literature treats the network as unipartite (as we do) because the structure of the unipartite network is substantively interesting (Fowler 2006; Zhang et al. 2007; Faust and Skvoretz 2002). network.”