R package for fitting topic models.
Update: We changed the name of this repo from 'LDAviz' to 'LDAtools' on 5/5/2014. It will remain a repo with tools for preprocessing raw text and fitting LDA topic models in R (with C code as the back-end to run the collapsed Gibbs sampler). Two notes:
For visualizing the output of a topic model, please check out our repo LDAvis, hosted by Carson Sievert. All future work on visualizing topic models will be done in this repo.
For fitting topic models, there are other software packages available, including MALLET and the R packages 'topicmodels' and 'lda', that are much more popular and better-tested (for speed and accuracy) than this package. This package was developed, more or less, (1) for practice building an R package and (2) to learn about LDA, rather than to become a widely-used package for others. So thanks for checking this out, but we'd recommend MALLET or other existing R packages for fitting topic models, and LDAvis for visualizing topic models.
library(devtools); install_github("LDAtools", "kshirley"); library(LDAtools)
Run AP example locally:
Make sure you have the following packages installed:
install.packages(c("plyr","reshape", "proxy", "shiny"))
library(shiny); runApp(system.file('shiny', 'hover', package='LDAtools'))
More documentation to come...