方法证据记录
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.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Wordfish
分类方法记录 · latent-structure / psychometrics
- 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
精选声明
声明已持久化到证据分类账中,每个声明都有自己的评估。
尚无精选声明
当分类账中没有声明时,此视图不会自行创建声明评估。
相关方法
从方法图中生成,显示为机器建议的关系 — 不推断任何证据声明。