Abstract
In recent years, political scientists increasingly have used data-science tools to research political processes, positions, and behaviors. Because both domestic and international politics are grounded in oral and written texts, computerized text analysis (CTA) - typically based on natural-language processing - has become one of the most notable applications of data-science tools in political research. This article explores the promises and perils of using CTA methods in political research and, specifically, the study of international relations. We highlight fundamental analytical and methodological gaps that hinder application and review processes. Whereas we acknowledge the significant contribution of CTA to political research, we identify a dual "engagement deficit"that may distance those without prior background in data science: (1) the tendency to prioritize methodological innovation over analytical and theoretical insights; and (2) the scholarly and political costs of requiring high proficiency levels and training to comprehend, assess, and use advanced research models.
| Original language | English |
|---|---|
| Pages (from-to) | 809-814 |
| Number of pages | 6 |
| Journal | PS - Political Science and Politics |
| Volume | 55 |
| Issue number | 4 |
| DOIs | |
| State | Published - 23 Oct 2022 |
Bibliographical note
Publisher Copyright:© 2022 The Author(s).
Funding
For helpful comments and suggestions, the authors thank Jonathan Grossman, Mathis Lohaus, and the panel participants and audience at the 2021 Virtual International Studies Association Conference, as well as the anonymous reviewers and PS: Political Science & Politics editors. This article is part of the research project, “What Are States Talking About?” (ISF Grant 2109/19), funded by the Israeli Science Foundation.
| Funders | Funder number |
|---|---|
| Israel Science Foundation | 2109/19 |