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.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- 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 10.1111/j.1540-5907.2008.00338.x
- Proksch, S. O., & Slapin, J. B. (2009). How to avoid pitfalls in statistical machine learning for social science. Political Analysis, 20(3), 343-357. · URL
- 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
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.