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Pinpointing the Powerful: Covoting Network Centrality as a Measure of Political Influence
Author(s) -
Ringe Nils,
Wilson Steven L.
Publication year - 2016
Publication title -
legislative studies quarterly
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.728
H-Index - 54
eISSN - 1939-9162
pISSN - 0362-9805
DOI - 10.1111/lsq.12129
Subject(s) - centrality , construct (python library) , measure (data warehouse) , voting , parliament , politics , katz centrality , network theory , political science , computer science , positive economics , social psychology , psychology , economics , data mining , law , betweenness centrality , mathematics , statistics , programming language
This article introduces centrality in covoting networks as a measure of influence. Based on a simple cueing dynamic, it conceptualizes those lawmakers as most central—and thus as having the greatest signaling influence —who impact the greatest number of colleagues' voting decisions. A formal proof and an agent‐based simulation show that cue‐providers are always more central than followers; hence, we can use real‐world voting data to identify the most influential legislators. To confirm the measure's construct validity, we predict covoting centrality in the European Parliament and find those factors that are expected to impact legislators' influence to predict their centrality.