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Measuring Political Positions from Legislative Speech

Published online by Cambridge University Press:  04 January 2017

Benjamin E. Lauderdale*
Affiliation:
Department of Methodology, London School of Economics, Houghton Street, London WC2A 2AE, UK
Alexander Herzog
Affiliation:
School of Computing, Clemson University, Clemson, SC 29634, USA, e-mail: aherzog@clemson.edu
*
e-mail: b.e.lauderdale@lse.ac.uk (corresponding author)

Abstract

Existing approaches to measuring political disagreement from text data perform poorly except when applied to narrowly selected texts discussing the same issues and written in the same style. We demonstrate the first viable approach for estimating legislator-specific scores from the entire speech corpus of a legislature, while also producing extensive information about the evolution of speech polarization and politically loaded language. In the Irish Dáil, we show that the dominant dimension of speech variation is government–opposition, with ministers more extreme on this dimension than backbenchers, and a second dimension distinguishing between the establishment and anti-establishment opposition parties. In the U. S. Senate, we estimate a dimension that has moderate within-party correlations with scales based on roll-call votes and campaign donation patterns; however, we observe greater overlap across parties in speech positions than roll-call positions and partisan polarization in speeches varies more clearly in response to major political events.

Type
Articles
Copyright
Copyright © The Author 2016. Published by Oxford University Press on behalf of the Society for Political Methodology 

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Footnotes

Authors’ note: Replication materials are available online as Lauderdale and Herzog (2016). We thank Ken Benoit, Royce Carroll, Justin Grimmer, Paul Kellstedt, Lanny Martin, Scott Moser, Adam Ramey, Randy Stevenson, Georg Vanberg, two anonymous reviewers, and the editor of this journal for their comments and feedback. Supplementary materials for this article are available on the Political Analysis Web site.

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