Estimation of the Structural Topic Model

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) and Roberts et al (2016) .


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Reference manual

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install.packages("stm")

1.3.3 by Brandon Stewart, a month ago


http://structuraltopicmodel.com


Report a bug at https://github.com/bstewart/stm/issues


Browse source code at https://github.com/cran/stm


Authors: Margaret Roberts [aut, cre], Brandon Stewart [aut, cre], Dustin Tingley [aut, cre], Kenneth Benoit [ctb]


Documentation:   PDF Manual  


Task views: Natural Language Processing


MIT + file LICENSE license


Imports matrixStats, splines, slam, lda, quanteda, stringr, Matrix, glmnet, Rcpp, grDevices, graphics, stats, utils, data.table, quadprog, parallel, methods

Suggests igraph, SnowballC, tm, huge, clue, wordcloud, KernSmooth, NLP, LDAvis, geometry, Rtsne, testthat, rsvd

Linking to Rcpp, RcppArmadillo


Imported by stmCorrViz, themetagenomics.

Depended on by stmgui.

Suggested by tidytext.


See at CRAN