The social identity voting model: Ideology and community structures

Abstract

Social identity voting (SIV) is a new model of voting behavior based on the principles of social identity theory. We introduce and use this model to analyze roll call votes for the 35 th through 112 th US Congresses. Comparing out-of-sample accuracy of SIV and Poole and Rosenthal's Weighted NOMINAL Three-step Estimation (W-NOMINATE), we find that SIV performs better than the one-or two-dimensional W-NOMINATE model and that generally, W-NOMINATE needs up to 10 dimensions to produce accuracy comparable to that of SIV. The differences between SIV and W-NOMINATE are further clarified in three case studies: first, a longitudinal examination of all Congresses; second, an analysis of the 112 th House of Representatives; and third, a study of the Tea Party caucus in the 112 th House of Representatives. Each study sheds new light on the potential motivations driving voting behavior, supporting our assertion that the SIV and W-NOMINATE models provide two distinct approaches to understanding voting records. SIV, with its emphasis on political identity derived from group membership, expresses combinations of individual and group preferences which contribute to legislators' ideological classifications.

Maximum a Posteriori Inference of Random Dot Product Graphs via Conic Programming

“…We choose this session as all n = 100 senators were active throughout the entire session. Similar latent space models [30,31] and network analyses of community detection from voting data have been studied in [19,25,26,27,32,40]. The edge probability P ij is defined to be the fraction of votes in which i and j voted the same way.…”

Do Birds of a Feather Vote Together, or Is It Peer Influence?

“…Despite the many insights that have been gleaned from examining formal rules, scholars frequently ignore informal social rules in legislative settings (Carey and Siavelis 2006). There are many exceptions, with a growing and committed group of scholars taking up this question, more often than not in the American subfield (Bogue and Marlaire 1975; Caldeira and Patterson 1987; Matthews 1959; Pauls, Leibon, and Rockmore 2015; Rogowski and Sinclair 2012; Routt 1938). Much of this work demonstrates the hidden power of interpersonal influence in policymaking.…”

“…There is an abundant literature on the effects of institutions on legislative behavior, but a relatively smaller, though important, literature concerning the relational or informal underpinnings of legislative behavior (Bogue and Marlaire 1975; Caldeira and Patterson 1987; Matthews 1959; Pauls, Leibon, and Rockmore 2015; Rogowski and Sinclair 2012; Routt 1938). Political science has made progress in this area, but it remains unclear to what extent social ties make a substantive difference in voting decisions, especially outside the U.S. context.…”

A Random Dot Product Model for Weighted Networks

“…Standard null models in this area may permute the edge weights (see e.g., [39]) or randomly reassign according to some distributional considerations (see e.g., [10,30]). Generalizing tools that have been developed for simple networks to weighted or multilayer networks is an active and important area of study [13,27,33].…”