日本語
 
Help Privacy Policy ポリシー/免責事項
  詳細検索ブラウズ

アイテム詳細


公開

学術論文

Validating Wordscores: The Promises and Pitfalls of Computational Text Scaling

MPS-Authors
/persons/resource/persons229348

Gemenis,  Kostas
Politische Ökonomie von Wachstumsmodellen, MPI for the Study of Societies, Max Planck Society;

Fulltext (restricted access)
There are currently no full texts shared for your IP range.
フルテキスト (公開)
公開されているフルテキストはありません
付随資料 (公開)
There is no public supplementary material available
引用

Bruinsma, B., & Gemenis, K. (2019). Validating Wordscores: The Promises and Pitfalls of Computational Text Scaling. Communication Methods and Measures, 13(3), 212-227. doi:10.1080/19312458.2019.1594741.


引用: https://hdl.handle.net/21.11116/0000-0003-739B-D
要旨
Wordscores is a popular computational text analysis method with numerous applications in communication research. Wordscores claims to scale documents on specified dimensions without requiring researchers to read or even understand the language of the input text. We investigate whether Wordscores delivers this claim by scaling the Euromanifestos of 117 political parties across 23 countries on 4 salient dimensions of political conflict. We assess validity by comparing the Wordscores estimates to expert surveys and other judgmental measures, and by examining the Wordscores’s estimates ability to predict party membership in the European Parliament groups. We find that the Wordscores estimates correlate poorly with expert and judgmental measures of party positions, while the latter outperform Wordscores in the predictive validity test. We conclude that Wordscores does not live up to its original claim of a “quick and easy” language blind method, and urge researchers to demonstrate the validity of the method in their domain of interest before any empirical analysis.