Latent structureText Scaling

Wordfish

Wordfish is a statistical model for scaling documents on latent dimensions, developed by Slapin and Proksch (2008). Unlike reference-based methods like Wordscores, Wordfish uses a Poisson generative model to jointly estimate word frequencies and document positions without requiring reference texts or manual annotation. It is particularly useful for estimating time-series changes in policy positions and can scale documents from multiple languages simultaneously.

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Sources

  1. Slapin, J. B., & Proksch, S. O. (2008). A scaling model for estimating time-series party positions from texts. Journal of Politics, 70(3), 554-569. DOI: 10.1017/S0022381608080523
  2. Proksch, S. O., & Slapin, J. B. (2009). How to avoid pitfalls in statistical machine learning for social science. Political Analysis, 20(3), 343-357. DOI: 10.1093/pan/mpr023
  3. Benoit, K., Muhr, D., & Spirling, A. (2016). Crowd-sourced text analysis: Reproducible and distributed production of political data. American Political Science Review, 110(2), 278-295. DOI: 10.1017/S0003055416000058

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Referenced by

ScholarGateWordfish (Wordfish). Retrieved 2026-06-04 from https://scholargate.app/en/psychometrics/wordfish