# juliasilge/tidytext

Text mining using tidy tools :sparkles::page_facing_up::sparkles:

Repository: https://github.com/juliasilge/tidytext
Canonical: https://ross.abutalabs.com/products/tidytext
Homepage: https://juliasilge.github.io/tidytext/
Language: R
License: NOASSERTION
License Family: other
Topics: text-mining, r, tidyverse, tidy-data, natural-language-processing
Last push: 2026-08-02T19:37:32+00:00

## Health v2 (maintenance only)
Score: 66/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 95, release rhythm 8, longevity 100
- inputs: {"age_days": 3807, "days_push": 31, "days_rel": 404, "gap_med": null, "n_releases_24m": 1}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1201, forks 181 (observed 2026-08-28T04:03:58.145534+00:00)

## What it is
tidytext is an R package that applies tidy data principles to text mining, providing functions like unnest_tokens to convert text to and from tidy data frames. It integrates with dplyr, tidyr, broom, and ggplot2, and bridges to existing text mining packages and formats like document-term matrices.

## Use cases
- tokenize text into tidy data frames in R
- compute tf-idf for term frequencies across documents
- do sentiment analysis on text corpora with tidy tools
- convert between tidy text format and document-term matrices
- analyze n-grams and word frequencies in R
- tidy topic modeling outputs for ggplot2 visualization

## When to choose
- you work in R with tidyverse tools and need text mining
- you want text analysis results as tidy data frames for dplyr/ggplot2 workflows
- you need to interoperate with tm or quanteda-style corpus and DTM objects

## When to avoid
- you need deep learning or transformer-based NLP
- you work outside R or prefer spaCy/NLTK pipelines
- you need production-scale streaming text processing

## Facets
- artifact type: library
- maturity: stable
- function: nlp, parser, data-science
- domain: data-science
- platform: python
- tags: r, tidyverse, text-mining, tokenization, sentiment-analysis, tf-idf, cran, natural-language-processing

## Member repositories
- juliasilge/tidytext (main) score 66

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:58.145534+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:20:42.207585+00:00, confidence not recorded.
  - readme: https://github.com/juliasilge/tidytext (fetched 2026-08-28T04:03:58.145534+00:00, sha e855844ee045)
  - homepage: https://juliasilge.github.io/tidytext/ (fetched 2026-08-29T12:27:49.165181+00:00, sha ba573f6f3ce4)
- Data as of 2026-08-30T08:39:29.467469+00:00.