# cjhutto/vaderSentiment

VADER Sentiment Analysis. VADER (Valence Aware Dictionary and sEntiment Reasoner) is a lexicon and rule-based sentiment analysis tool that is specifically attuned to sentiments expressed in social media, and works well on texts from other domains.

Repository: https://github.com/cjhutto/vaderSentiment
Canonical: https://ross.abutalabs.com/products/vadersentiment
Language: Python
License: MIT
License Family: permissive
Last push: 2026-03-02T15:09:02+00:00

## Health v2 (maintenance only)
Score: 54/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 70, release rhythm 8, longevity 100
- inputs: {"age_days": 4307, "days_push": 184, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 5053, forks 1056 (observed 2026-08-28T04:09:09.106723+00:00)

## What it is
VADER is a lexicon and rule-based sentiment analysis library for Python, specifically tuned to sentiments expressed in social media but effective on other text domains. It handles negations, punctuation intensity, slang, emoticons, and emojis, and is also integrated into NLTK.

## Use cases
- analyze sentiment of tweets and social media posts
- score sentiment of product reviews
- detect sentiment in text with emojis and emoticons
- handle negations like 'not good' in sentiment scoring
- run sentence-level sentiment analysis on longer documents
- get quick sentiment scores without training a machine learning model

## When to choose
- you need fast, dependency-light sentiment scoring without training data
- your text comes from social media with slang, emojis, and casual language
- you want interpretable, rule-based sentiment results

## When to avoid
- you need state-of-the-art accuracy on complex or domain-specific text
- you need aspect-based or multilingual sentiment analysis out of the box
- you require contextual understanding that only transformer models provide

## Facets
- artifact type: library
- maturity: stable
- function: nlp, parser
- domain: social-media, data-science
- platform: python, cross-platform
- tags: sentiment-analysis, lexicon-based, social-media, rule-based, text-analysis, natural-language-processing

## Member repositories
- cjhutto/vaderSentiment (main) score 54

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:09.106723+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 2026-08-29T18:17:20.533312+00:00, confidence not recorded.
  - readme: https://github.com/cjhutto/vaderSentiment (fetched 2026-08-28T04:09:09.106723+00:00, sha b23e5a12de74)
  - registry_pypi: https://pypi.org/pypi/vadersentiment/json (fetched 2026-08-29T08:57:44.077079+00:00, sha 36d04935dd9f)
- Data as of 2026-08-30T08:39:29.467469+00:00.