Same model, same numbers | Topic labels (probability, FREX, lift, score) | Semantic coherence and exclusivity | Different fit, comparable quality | What this means for your analysis

Multiple content covariates | Framing, not agenda | estimateEffect(): cluster-robust SEs and weights | Random effects in prevalence | Average marginal effects | Topic prevalence over time | Coherence: NPMI and C_V | A tidyverse-friendly surface | Summary

Ingesting data | Estimating the structural topic model | Model selection and search | Interpreting topics | Covariate effects on topic prevalence | Topical content | Interactions | More visualization | Out-of-sample documents