The Structural Topic Model (STM) allows researchers to estimate topic models with document-level covariates. The package also includes tools for model selection, visualization, and estimation of topic-covariate regressions. Methods developed in Roberts et. al. (2014) <doi:10.1111/ajps.12103> and Roberts et. al. (2016) <doi:10.1080/01621459.2016.1141684>. Vignette is Roberts et. al. (2019) <doi:10.18637/jss.v091.i02>.
| Version: | 1.3.8 |
| Depends: | R (≥ 3.5.0), methods |
| Imports: | Rcpp (≥ 0.11.3),data.table,glmnet, grDevices, graphics,lda,Matrix,matrixStats, parallel,quadprog,quanteda,slam, splines, stats,stringr, utils |
| LinkingTo: | Rcpp,RcppArmadillo |
| Suggests: | clue,geometry,huge,hunspell,igraph,LDAvis,KernSmooth,NLP,rsvd,Rtsne,SnowballC,spelling,testthat,tm (≥ 0.6),wordcloud |
| Published: | 2025-09-03 |
| DOI: | 10.32614/CRAN.package.stm |
| Author: | Margaret Roberts [aut], Brandon Stewart [aut, cre], Dustin Tingley [aut], Kenneth Benoit [ctb] |
| Maintainer: | Brandon Stewart <bms4 at princeton.edu> |
| BugReports: | https://github.com/bstewart/stm/issues |
| License: | MIT + fileLICENSE |
| URL: | http://www.structuraltopicmodel.com/ |
| NeedsCompilation: | yes |
| Language: | en-US |
| Citation: | stm citation info |
| Materials: | NEWS |
| In views: | NaturalLanguageProcessing |
| CRAN checks: | stm results |