chicago-justice-project/article-tagging

Natural Language Processing of Chicago news articles

46
/ 100
Emerging

This tool helps researchers and journalists studying crime in Chicago to automatically categorize news articles by type of crime (e.g., homicide, arson, gun violence). It takes raw news article text as input and outputs relevant crime tags, as well as extracts locations mentioned and provides their geographic coordinates and community areas. It is designed for data analysts, criminologists, and investigative journalists working with large volumes of local news content.

No commits in the last 6 months.

Use this if you need to quickly process many Chicago news articles to understand crime reporting patterns and geographically map crime mentions.

Not ideal if you require perfect accuracy for every single article or are analyzing news outside of Chicago, as the models are trained on Chicago-specific data.

criminology journalism urban-studies public-policy geographic-analysis
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 20 / 25

How are scores calculated?

Stars

51

Forks

25

Language

Jupyter Notebook

License

MIT

Last pushed

Sep 14, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/nlp/chicago-justice-project/article-tagging"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.