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Estimating text regressions using txtreg_train

Author

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  • Carlo Schwarz

    (Bocconi University)

Abstract

In this article, I introduce new commands to estimate text regressions for continuous, binary, and categorical variables based on text strings. The command txtreg_train automatically handles text cleaning, tokenization, model training, and cross-validation for lasso, ridge, elastic-net, and regularized logis- tic regressions. The txtreg_predict command obtains the predictions from the trained text regression model. Furthermore, the txtreg_analyze command facil- itates the analysis of the coefficients of the text regression model. Together, these commands provide a convenient toolbox for researchers to train text regressions. They also allow sharing of pretrained text regression models with other researchers.

Suggested Citation

  • Carlo Schwarz, 2023. "Estimating text regressions using txtreg_train," Stata Journal, StataCorp LP, vol. 23(3), pages 799-812, September.
  • Handle: RePEc:tsj:stataj:v:23:y:2023:i:3:p:779-812
    DOI: 110.1177/1536867X231196349
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    Cited by:

    1. Jiménez Durán, Rafael & Muller, Karsten & Schwarz, Carlo, 2024. "The Effect of Content Moderation on Online and Offline Hate: Evidence from Germany’s NetzDG," CAGE Online Working Paper Series 701, Competitive Advantage in the Global Economy (CAGE).

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