# juliasilge/tidy-text-mining

Manuscript of the book "Tidy Text Mining with R" by Julia Silge and David Robinson

Repository: https://github.com/juliasilge/tidy-text-mining
Canonical: https://ross.abutalabs.com/products/tidy-text-mining
Homepage: http://tidytextmining.com
Language: TeX
License: NOASSERTION
License Family: other
Topics: book, text-mining, tidyverse, bookdown, r
Last push: 2025-04-06T23:56:14+00:00

## Health v2 (maintenance only)
Score: 39/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 15, release rhythm 35, longevity 100
- inputs: {"age_days": 3710, "days_push": 514, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1376, forks 803 (observed 2026-08-28T04:04:33.204308+00:00)

## What it is
The open-source manuscript of the book 'Text Mining with R: A Tidy Approach' by Julia Silge and David Robinson, written in bookdown/TeX. It teaches text mining and natural language processing in R using tidyverse tools.

## Use cases
- learn text mining in R
- tidy text analysis tutorial
- sentiment analysis with tidytext
- topic modeling with R
- n-gram and tf-idf analysis in R
- free book on text mining with tidyverse

## When to choose
- you want to learn text mining using R and the tidyverse
- you need a free, well-regarded reference for tidytext workflows
- you are teaching or self-studying NLP basics in R

## When to avoid
- you need a production NLP library rather than learning material
- you work primarily in Python or another language
- you need commercial-use licensed content (CC-BY-NC-SA)

## Facets
- artifact type: learning-resource
- maturity: stable
- function: nlp, data-science, documentation
- domain: data-science, tutorials
- platform: python
- tags: r, tidyverse, bookdown, text-mining, book, natural-language-processing

## Member repositories
- juliasilge/tidy-text-mining (main) score 39

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:33.204308+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 2026-08-30T04:40:30.310758+00:00, confidence not recorded.
  - readme: https://github.com/juliasilge/tidy-text-mining (fetched 2026-08-28T04:04:33.204308+00:00, sha 48f96baf892a)
  - homepage: http://tidytextmining.com (fetched 2026-08-29T11:56:44.537353+00:00, sha 45da7b6aef82)
- Data as of 2026-08-30T08:39:29.467469+00:00.