# corollari/linusrants

Dataset of Linus Torvalds' rants classified by negativity using sentiment analysis

Repository: https://github.com/corollari/linusrants
Canonical: https://ross.abutalabs.com/products/linusrants
Language: Python
License Family: other
Topics: linus-rants, dataset, sentiment-analysis, linus-torvalds, linus
Last push: 2020-09-15T18:40:24+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3081, "days_push": 2178, "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 1880, forks 36 (observed 2026-08-28T04:05:48.472150+00:00)

## What it is
A dataset of Linus Torvalds' rants from the Linux kernel mailing list (2012-2015), classified by negativity using sentiment analysis. It is available in JSON, TSV, pickle, and table formats with hate-score metadata.

## Use cases
- analyze sentiment of Linus Torvalds' mailing list rants
- train or evaluate sentiment analysis models on colorful text
- find the most negative kernel mailing list posts
- plot or visualize rant negativity over time
- study profanity and tone in open-source communication

## When to choose
- you need a labeled text dataset for sentiment analysis experiments
- you want to analyze or plot Linus Torvalds' rants with metadata
- you're building NLP tutorials or demos on real-world text

## When to avoid
- you need current or post-2015 mailing list data
- you need a production software tool rather than a static dataset
- you require a maintained, licensed project for commercial use

## Facets
- artifact type: dataset
- maturity: maintenance
- function: nlp, data-science
- domain: data-science, developer-tools
- platform: python
- tags: sentiment-analysis, linus-torvalds, linux-kernel, mailing-list, text-classification, natural-language-processing

## Member repositories
- corollari/linusrants (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:48.472150+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 2026-08-30T03:14:00.249314+00:00, confidence not recorded.
  - readme: https://github.com/corollari/linusrants (fetched 2026-08-28T04:05:48.472150+00:00, sha 502049ee90c9)
- Data as of 2026-08-30T08:39:29.467469+00:00.