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Measuring Elite Personality Using Speech

Published online by Cambridge University Press:  18 March 2016

Adam J. Ramey ,
Jonathan D. Klingler  and
Gary E. Hollibaugh Jr
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Abstract

We apply recent advances in machine learning to measure Congressmember personality traits using floor speeches from 1996 to 2014. We also demonstrate the superiority of text-based measurement over survey-based measurement by showing that personality traits are correlated with survey response rates for members of Congress. Finally, we provide one empirical application showcasing the importance of personality on congressional behavior.

Type
Original Articles
Information
Political Science Research and Methods , Volume 7 , Issue 1 , January 2019 , pp. 163 - 184
Copyright
© The European Political Science Association 2016 

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Footnotes

*

Adam J. Ramey is an Assistant Professor of Politics, New York University Abu Dhabi, PO Box 129188, Abu Dhabi ([email protected]). Jonathan D. Klingler is a Postdoctoral Fellow in the Institute for Advanced Study in Toulouse, Université Toulouse 1 Capitole, 21 alleé de Brienne, 31000 Toulouse ([email protected]). Gary E. Hollibaugh, Jr. is an Assistant Professor in the Department of Political Science, University of Notre Dame, Notre Dame, IN 46556 ([email protected]). All authors contributed equally to the paper. Support through ANR-Labex IAST is gratefully acknowledged. The authors thank Ken Benoit, Matt Blackwell, Richard Bonneau, Drew Dimmery, Conor Dowling, Michael Gill, Andy Harris, Pablo Hernandez-Lagos, John Jost, Slava Mihkaylov, Jeff Mondak, Jonathan Nagler, David Nickerson, Elena Panova, John Patty, Michael Peress, Dave Primo, Molly Roberts, Larry Rothenberg, Maya Sen, Jo Silvester, Arthur Spirling, Karine van der Straeten, and participants at the 5th Annual Text as Data Conference and the Rooney Center for the Study of American Democracy for comments and feedback. All remaining errors are their own. To view supplementary material for this article, please visit http://dx.doi.org/10.1017/psrm.2016.12

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