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.
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| tidytext | Text mining using dplyr, ggplot2, and other tidy tools |
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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 |
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| textTinyR | Text processing for small or big data |
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Read our verdict in the software roundup.
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