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.

Install the latest version of this package by entering the following in R:
install.packages("LDAvis")
AuthorCarson Sievert [aut, cre], Kenny Shirley [aut]
Date of publication2015-10-24 08:21:16
MaintainerCarson Sievert <cpsievert1@gmail.com>
LicenseMIT + file LICENSE
Version0.3.2
https://github.com/cpsievert/LDAvis

View on CRAN

Files

inst
inst/htmljs
inst/htmljs/index.html
inst/htmljs/ldavis.js
inst/htmljs/d3.v3.js
inst/htmljs/lda.css
inst/shiny
inst/shiny/shinyLDAvis.js
inst/doc
inst/doc/details.pdf
inst/doc/details.Rnw
NAMESPACE
NEWS
data
data/TwentyNewsgroups.rda
R
R/createJSON.R R/data.R R/shiny.R R/serVis.R R/imports.R R/runShiny.R
vignettes
vignettes/details.Rnw
README.md
MD5
build
build/vignette.rds
DESCRIPTION
man
man/TwentyNewsgroups.Rd man/jsPCA.Rd man/serVis.Rd man/runShiny.Rd man/visOutput.Rd man/createJSON.Rd man/renderVis.Rd
LICENSE

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.