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: 3.0.4
Depends: R (≥ 3.0.2), Matrix
Imports: gtools, magrittr, methods, parallel, text2vec (≥ 0.5), stopwords, stringr, Rcpp, RcppProgress, RSpectra
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
Suggests: digest, dplyr, igraph, knitr, lda, MASS, rmarkdown, SnowballC, stringi, testthat, tibble, tidyr, tidytext, topicmodels, wordcloud
Published: 2019-04-18
Author: Tommy Jones [aut, cre], William Doane [ctb]
Maintainer: Tommy Jones <jones.thos.w at gmail.com>
BugReports: https://github.com/TommyJones/textmineR/issues
License: MIT + file LICENSE
URL: https://www.rtextminer.com/
NeedsCompilation: yes
SystemRequirements: GNU make, C++11
Materials: README NEWS
CRAN checks: textmineR results


Reference manual: textmineR.pdf
Vignettes: 1. Start here
2. document clustering
3. Topic modeling
4. Text embeddings
5. Document summarization
6. Using tidytext with textmineR
Package source: textmineR_3.0.4.tar.gz
Windows binaries: r-devel: textmineR_3.0.4.zip, r-release: textmineR_3.0.4.zip, r-oldrel: textmineR_3.0.4.zip
macOS binaries: r-release: textmineR_3.0.4.tgz, r-oldrel: textmineR_3.0.4.tgz
Old sources: textmineR archive

Reverse dependencies:

Reverse suggests: mvrsquared


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