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Using Motion Detection to Measure Social Polarization in the U.S. House of Representatives

Published online by Cambridge University Press:  11 November 2020

Bryce J. Dietrich*
Department of Political Science, University of Iowa, 341 Schaeffer Hall, Iowa City, IA 52242, USA. Email:
Corresponding author Bryce J. Dietrich


Although previous scholars have used image data to answer important political science questions, less attention has been paid to video-based measures. In this study, I use motion detection to understand the extent to which members of Congress (MCs) literally cross the aisle, but motion detection can be used to study a wide range of political phenomena, like protests, political speeches, campaign events, or oral arguments. I find not only are Democrats and Republicans less willing to literally cross the aisle, but this behavior is also predictive of future party voting, even when previous party voting is included as a control. However, this is one of the many ways motion detection can be used by social scientists. In this way, the present study is not the end, but the beginning of an important new line of research in which video data is more actively used in social science research.

© The Author(s) 2020. Published by Cambridge University Press on behalf of the Society for Political Methodology

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Edited by Jeff Gill


The keywords have been corrected. A corrigendum notice detailing this change was also published (DOI: 10.1017/pan.2021.8).


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