tidytext serves to bring text data into the “tidyverse”.
It’s text mining for word processing and sentiment analysis using ‘dplyr’, ‘ggplot2’, and other tidy tools.
It provides simple tools to manipulate unstructured text data in such a way that it can be analyzed with tools like dplyr and ggplot2.
The tidytext package structures text data upon the principle of tidy data. As well documented in a chapter of Hadley Wickham’s R for Data Science, three rules make a data set tidy:
- Each variable must have its own column.
- Each observation must have its own row.
- Each value must have its own cell.
Website: juliasilge.github.io/tidytext
Support: GitHub Code Repository
Developer: Julia Silge, David Robinson
License: MIT License
tidytext is written in R. Learn R with our recommended free books and free tutorials.
Related Software
| Natural Language Processing | |
|---|---|
| PyTorch-Transformers | Library of state-of-the-art pre-trained models |
| Natural Language Toolkit | Suite of open source Python modules, data sets and tutorials |
| Stanford CoreNLP | Extensible annotation-based NLP pipeline |
| spaCy | Industrial strength natural language processing |
| scikit-learn | Machine learning library for Python |
| Gensim | Python-based vector space modeling and topic modeling toolkit |
| flair | Simple framework for state-of-the-art NLP |
| Apache OpenNLP | Machine learning based toolkit |
| DL4J | Deploy and train deep learning models |
| Apache Lucene | Full-featured information retrieval software library |
| UIMA | Implementation of the UIMA specification |
| tidytext | Text mining using dplyr, ggplot2, and other tidy tools |
| text2vec | Framework with API for text analysis and NLP |
| quanteda | R package for Quantitative Analysis of Textual Data |
| Moses | Statistical machine translation system |
Read our verdict in the software roundup.
| R Natural Language Processing Tools | |
|---|---|
| tidytext | Text mining using dplyr, ggplot2, and other tidy tools |
| quanteda | R package for Quantitative Analysis of Textual Data |
| text2vec | Framework with API for text analysis and natural language processing |
| wordcloud | Create attractive word clouds |
| tm | Text Mining Infrastructure in R |
| srtringi | Fast and portable character string processing in R |
| Stringr | String manipulation in R |
| UDPipe | Tokenization, Tagging, Lemmatization and Dependency Parsing |
| tokenizers | Convert natural language text into tokens |
| spacyr | R wrapper around the Python spaCy package |
| Word Vectors | Build and explore embedding models |
| syuzhet | Extraction of sentiment and sentiment-based plot arcs from text |
| textTinyR | Text processing for small or big data |
| sentimentr | Dictionary based sentiment analysis |
| textclean | Collection of tools to clean and normalize text |
| TALL | Explore, model, and visualize textual data |
| corpustools | Various tools for analyzing text corpora |
| topicmodels | Interface to LDA and CTM models |
| text | Analyzing natural language with transformers-based large language models |
| RTextTools | Automatic text classification via supervised learning |
Read our verdict in the software roundup.
 LinuxLinks helps you discover the best free and open source software for Linux. Explore our extensive collection of recommended applications, including alternatives to popular proprietary software.We also publish software reviews, Linux tutorials, hardware reviews, free programming books and articles covering the wider open source community. Browse our Linux resources to discover more. Know a useful free and open source Linux application we haven't covered? Suggest a program for inclusion. Has your software been featured on LinuxLinks? Display one of our Featured on LinuxLinks badges on your website or GitHub README. |
Please read our Comment Policy before commenting.