Text Analysis

R package to manipulate and analyze text data using tidy data principles.

A text mining framework for pre-processing, filtering, and analyzing large text corpora in R.

R package that implements algorithms like LDA (latent Dirichlet allocation) for discovering latent topics in text collections.

An R package for Biterm Topic Modeling, especially suited for short texts like tweets.

R package that provides Gibbs sampling implementations of LDA (latent Dirichlet allocation) for topic modeling.

R package that fits topic models that incorporate document-level metadata to influence topic prevalence or content.

R package that provides access to Apache OpenNLP tools for POS (part of speech) tagging, sentence splitting, named entity recognition, and more.

A simple tool for generating word clouds based on term frequency in R.

R tools for statistical modeling of word frequency distributions, based on Zipf's law.

High-performance tools for text vectorization, similarity, and classification in R.

R package providing rule-based sentiment analysis for financial, product, or general text corpora.