Computer-Assisted Text Analysis for Comparative Politics

Christopher Lucas · Richard A. Nielsen · Margaret E. Roberts · Brandon Stewart · Alex Storer · Dustin H. Tingley

478 citations0/0 files storedPolitical Analysis

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Computational and Text Analysis Methods Sentiment Analysis and Opinion Mining Political Science Research and Education

Abstract

Recent advances in research tools for the systematic analysis of textual data are enabling exciting new research throughout the social sciences. For comparative politics, scholars who are often interested in non-English and possibly multilingual textual datasets, these advances may be difficult to access. This article discusses practical issues that arise in the processing, management, translation, and analysis of textual data with a particular focus on how procedures differ across languages. These procedures are combined in two applied examples of automated text analysis using the recently introduced Structural Topic Model. We also show how the model can be used to analyze data that have been translated into a single language via machine translation tools. All the methods we describe here are implemented in open-source software packages available from the authors.

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1984Content Analysis: An Introduction to its Methodology.2013Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts 2014Structural Topic Models for Open‐Ended Survey Responses 2019stm : An R Package for Structural Topic Models 2003Extracting Policy Positions from Political Texts Using Words as Data 2008Text Mining Infrastructure in R 1966The general inquirer: A computer approach to content analysis.2011topicmodels : An R Package for Fitting Topic Models

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