Fightin' Words: Lexical Feature Selection and Evaluation for Identifying the Content of Political Conflict

Posted: 18 Aug 2009  

Burt L. Monroe

affiliation not provided to SSRN

Michael P. Colaresi

Michigan State University

Kevin M. Quinn

UC Berkeley School of Law

Date Written: Autumn 2008

Abstract

Entries in the burgeoning “text-as-data” movement are often accompanied by lists or visualizations of how word (or other lexical feature) usage differs across some pair or set of documents. These are intended either to establish some target semantic concept (like the content of partisan frames) to estimate word-specific measures that feed forward into another analysis (like locating parties in ideological space) or both. We discuss a variety of techniques for selecting words that capture partisan, or other, differences in political speech and for evaluating the relative importance of those words. We introduce and emphasize several new approaches based on Bayesian shrinkage and regularization. We illustrate the relative utility of these approaches with analyses of partisan, gender, and distributive speech in the U.S. Senate.

Suggested Citation

Monroe, Burt L. and Colaresi, Michael P. and Quinn, Kevin M., Fightin' Words: Lexical Feature Selection and Evaluation for Identifying the Content of Political Conflict (Autumn 2008). Political Analysis, Vol. 16, Issue 4, pp. 372-403, 2008. Available at SSRN: https://ssrn.com/abstract=1448450 or http://dx.doi.org/10.1093/pan/mpn018

Burt L. Monroe (Contact Author)

affiliation not provided to SSRN

No Address Available

Michael P. Colaresi

Michigan State University ( email )

East Lansing, MI 48824
United States

Kevin M. Quinn

UC Berkeley School of Law ( email )

215 Boalt Hall
Berkeley, CA 94720-7200
United States

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