LDAvis: Interactive Visualization of Topic Models

Tools to create an interactive web-based visualization of a topic model that has been fit to a corpus of text data using Latent Dirichlet Allocation (LDA). Given the estimated parameters of the topic model, it computes various summary statistics as input to an interactive visualization built with D3.js that is accessed via a browser. The goal is to help users interpret the topics in their LDA topic model.

Version: 0.3.2
Depends: R (≥ 2.10)
Imports: proxy, RJSONIO, parallel
Suggests: mallet, lda, topicmodels, gistr (≥, servr, shiny, knitr, rmarkdown, digest, htmltools
Published: 2015-10-24
Author: Carson Sievert [aut, cre], Kenny Shirley [aut]
Maintainer: Carson Sievert <cpsievert1 at gmail.com>
BugReports: https://github.com/cpsievert/LDAvis/issues
License: MIT + file LICENSE
URL: https://github.com/cpsievert/LDAvis
NeedsCompilation: no
Materials: README NEWS
CRAN checks: LDAvis results


Reference manual: LDAvis.pdf
Vignettes: LDAvis details
Package source: LDAvis_0.3.2.tar.gz
Windows binaries: r-devel: LDAvis_0.3.2.zip, r-release: LDAvis_0.3.2.zip, r-oldrel: LDAvis_0.3.2.zip
OS X binaries: r-release: LDAvis_0.3.2.tgz, r-oldrel: LDAvis_0.3.2.tgz
Old sources: LDAvis archive

Reverse dependencies:

Reverse suggests: stm, textmining


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