textmineR: Functions for Text Mining and Topic Modeling

An aid for text mining in R, with a syntax that should be familiar to experienced R users. Provides a wrapper for several topic models that take similarly-formatted input and give similarly-formatted output. Has additional functionality for analyzing and diagnostics for topic models.

Version: 3.0.1
Depends: R (≥ 3.0.2), Matrix
Imports: methods, parallel, text2vec (≥ 0.5), stopwords, stringr, Rcpp, RcppProgress, RSpectra
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
Suggests: digest, igraph, knitr, lda, MASS, rmarkdown, SnowballC, stringi, testthat, topicmodels, wordcloud
Published: 2018-10-31
Author: Thomas Jones [aut, cre], William Doane [ctb]
Maintainer: Thomas Jones <jones.thos.w at gmail.com>
BugReports: https://github.com/TommyJones/textmineR/issues
License: MIT + file LICENSE
URL: https://github.com/TommyJones/textmineR
NeedsCompilation: yes
SystemRequirements: GNU make, C++11
Materials: README
CRAN checks: textmineR results

Downloads:

Reference manual: textmineR.pdf
Vignettes: 1. Start here
2. document clustering
3. Topic modeling
4. Text embeddings
5. Document summarization
Package source: textmineR_3.0.1.tar.gz
Windows binaries: r-devel: textmineR_3.0.1.zip, r-release: textmineR_3.0.1.zip, r-oldrel: textmineR_3.0.1.zip
OS X binaries: r-release: textmineR_3.0.1.tgz, r-oldrel: textmineR_3.0.1.tgz
Old sources: textmineR archive

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