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.

Documentation

Manual: stm.pdf
Vignette: Using stm

Maintainer: Brandon Stewart <bms4 at princeton.edu>

Author(s): Margaret Roberts*, Brandon Stewart*, Dustin Tingley*, Kenneth Benoit*

Install package and any missing dependencies by running this line in your R console:

install.packages("stm")

Depends R (>= 2.10)
Imports matrixStats, splines, slam, lda, quanteda, stringr, Matrix, glmnet, Rcpp(>=0.11.3), grDevices, graphics, stats, utils, data.table, quadprog
Suggests igraph, SnowballC, tm(>=0.6), huge, clue, wordcloud, KernSmooth, NLP, LDAvis, geometry, Rtsne, testthat
Enhances
Linking to Rcpp, RcppArmadillo
Reverse
depends
stmgui
Reverse
imports
stmBrowser, stmCorrViz, themetagenomics
Reverse
suggests
Reverse
enhances
Reverse
linking to

Package stm
Materials
URL http://structuraltopicmodel.com
Task Views
Version 1.2.2
Published 2017-03-28
License MIT + file LICENSE
BugReports https://github.com/bstewart/stm/issues
SystemRequirements
NeedsCompilation yes
Citation
CRAN checks stm check results
Package source stm_1.2.2.tar.gz