kshirley/LDAtools: Tools to fit a topic model using Latent Dirichlet Allocation (LDA)

This package implements a collapsed Gibbs Sampler algorithm to fit a topic model to a set of unstructured text documents. It contains three basic groups of functions: (1) pre-processing of unstructured text, including substitutions, tokenization, and stemming, (2) fitting the Latent Dirichlet Allocation (LDA) topic model to training data and making model-based predictions on test data, and (3) visualizing and summarizing the fitted model.

install.packages("remotes")
remotes::install_github("kshirley/LDAtools")