Special Issue: The Statistical Analysis of Political Text
The Web revolutionized the availability of texts, providing material that was accessible, reasonably standardized in the form of HTML files, and, critically for academic researchers, free of charge. By the first decade of the 21st century, vast quantities of politically relevant texts were available, ranging from the rants of political bloggers to official campaign statements to parliamentary debates to day-to-day news reports. Although such sources cannot be immediately analyzed, tools for downloading and filtering web content have become increasingly common, user-friendly, and generalized, and once a system has been developed for a particular site, the marginal cost of acquiring additional data is usually close to zero. As a consequence of these developments, automated content analysis in political science has experienced considerable growth in recent years.
This special issue, guest edited by Burt L. Monroe and Philip A. Schrodt, focuses on fully automated methods. The techniques presented in this issue by no means exhaust the available methods, and the source texts explored in these studies are only a tiny fraction of those available. The editors' hope is that readers interested in these methods will use the approaches discussed here—as well as those referenced tangentially in many of the articles—as a jumping-off point for further research and development.
Table of Contents
Introduction to the Special Issue: The Statistical Analysis of Political Text
Burt L. Monroe and Philip A. Schrodt
Fightin' Words: Lexical Feature Selection and Evaluation for Identifying the Content of Political Conflict
Burt L. Monroe, Michael P. Colaresi, and Kevin M. Quinn
Does Deliberation Matter in FOMC Monetary Policymaking? The Volcker Revolution of 1979
Andrew Bailey and Cheryl Schonhardt-Bailey
Parsing, Semantic Networks, and Political Authority Using Syntactic Analysis to Extract Semantic Relations from Dutch Newspaper Articles
Wouter van Atteveldt, Jan Kleinnijenhuis, and Nel Ruigrok
Lexical Cohesion Analysis of Political Speech
Beata Beigman Klebanov, Daniel Diermeier, and Eyal Beigman
Coding Disaggregated Intrastate Conflict: Machine Processing the Behavior of Substate Actors Over Time and Space
Stephen M. Shellman
View the table of contents with abstracts here.
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