xpert-codes/Identifying-Toxic-Comments-And-Threats-On-Social-Media-Using-Machine-Learning-in-Python
View on GitHub ↗Related repositories →Social media had become a part in our daily life, unfortunately these platforms can occasionally contain threats and other elements of cyberbullying. The issue of identifying toxic comments and threats on social media was examined and we differentiated toxic classified comments from non toxic comments.
active 2024-02-28 → 2024-02-28 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2024-02-28 to 2024-02-28. Pushes: 0 total, peak 0 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
Nobody pushed, opened or commented here in the loaded window — this repo's activity is stars and forks only.
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.