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 (≥ 0.0.8.99), 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 |