Specifies and diagnoses structural topic models for survey and experimental text — choosing among STM, LDA, and BERTopic, preprocessing decisions and their consequences, prevalence and content formulas with spectral initialization and a recorded seed, selecting the topic count across semantic coherence, exclusivity and FREX, held-out likelihood, and residuals rather than one metric, interpretation and validation against representative documents, robustness checks, and DA-RT-compliant reporting.
mdr add scdenney/open-science-skills/topic-modeling@git:20260902.da5a263mdr add scdenney/open-science-skills/topic-modeling@sha256:14183e035347ddd6[](https://markdownregistry.com/a/art_ngqehyoehtkf25cn)
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| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260902.da5a263 latest | 2026-09-02 | da5a263 | 15,461 B | A | view · diff |
| git:20260702.0d142fe | 2026-07-02 | 0d142fe | 14,820 B | A | view |
scdenney/open-science-skills · 54 stars · license NOASSERTION · pushed 2026-09-05 · branch main
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