williamcsevier/textclass: Analytical Tool for Automated Text Analysis with Interpretable Graphical Output

The package will be able to accept .csv files containing text data and perform various text analysis procedures, with options to return the raw data for further manipulation, or ggplot graphics of the text analysis methods. This allows the user to easily analyze their text data without having to do any of the required preprocessing. In addition, even the most novice of data scientists can portray their text analysis results cleanly, with limited knowledge of R. Specifically, this package will give the user options to output most frequent terms, n-gram analysis, and topic modeling analysis. Topic modeling involved allowing the user to determine how many topics with which to model their topics, and output the most associated terms with each topics, as well word-word correlation, and document-topic association.

Getting started

Package details

AuthorCharter Sevier
MaintainerCharter Sevier <williamcsevier@gmail.com>
LicenseGPL (>=2)
Version0.1.0
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("williamcsevier/textclass")
williamcsevier/textclass documentation built on May 26, 2019, 5:36 a.m.