Fightin' Words: Lexical Feature Selection and Evaluation for Identifying the Content of Political Conflict
- 31 August 2008
- journal article
- research article
- Published by Cambridge University Press (CUP) in Political Analysis
- Vol. 16 (4), 372-403
- https://doi.org/10.1093/pan/mpn018
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.Keywords
This publication has 31 references indexed in Scilit:
- Classifying Party Affiliation from Political SpeechJournal of Information Technology & Politics, 2008
- Computer-Assisted Topic Classification for Mixed-Methods Social Science ResearchJournal of Information Technology & Politics, 2008
- The Congressional Debate on Partial-Birth Abortion: Constitutional Gravitas and Moral PassionBritish Journal of Political Science, 2008
- Understanding WordscoresPolitical Analysis, 2008
- Special issue on “Optofluidics”Microfluidics and Nanofluidics, 2007
- Framing TheoryAnnual Review of Political Science, 2007
- A probabilistic justification for using tf×idf term weighting in information retrievalInternational Journal on Digital Libraries, 2000
- A Decision-Theoretic Generalization of On-Line Learning and an Application to BoostingJournal of Computer and System Sciences, 1997
- Abortion: Evidence of an Issue EvolutionAmerican Journal of Political Science, 1997
- Bayesian Regularization and Pruning Using a Laplace PriorNeural Computation, 1995