SUBHADIPMAITI-DEV/Depression-Detection-System-Using-Machine-Learning
View on GitHub ↗Related repositories →This project develops a Depression Detection System using Machine Learning on Twitter data. It predicts depression by analyzing tweets with SVM, Logistic Regression, Decision Trees, and NLTK in Python.
active 2023-11-29 → 2026-04-14 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 868 days from 2023-11-29 to 2026-04-14. Pushes: 5 total, peak 2 in a day. Pull requests: 8 total, peak 4 in a day. Issues: 1 total, peak 1 in a day. Comments: 1 total, peak 1 in a day. Stars: 15 total, peak 2 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Stars, PRs, issues and forks are under-captured in the later part of this window. GH Archive progressively stopped capturing non-push events during 2026 — −95% or worse by the end of the window. Every series here except Pushes fades for that reason, so a decline above reflects the archive, not this repository. Pushes stay reliable throughout, so read them, and the contributor counts derived from them, as the real signal. Data health has the measurements.
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| SUBHADIPMAITI-DEV | 14 | 5 | 8 | 0 |
| gitguardian[bot] | 1 | 0 | 0 | 1 |
Recent activity
Latest issues, pull requests and releases
- Pull request#11SUBHADIPMAITI-DEV2024-07-26 06:19
- Pull request#11SUBHADIPMAITI-DEV2024-07-26 06:19
- Pull request#5SUBHADIPMAITI-DEV2024-07-16 05:57
- Pull request#5SUBHADIPMAITI-DEV2024-07-16 05:57
- Issue#4SUBHADIPMAITI-DEV2024-07-16 05:55Add your Issue
- Pull request#3SUBHADIPMAITI-DEV2024-07-16 05:54
- Issue comment#3gitguardian[bot]2024-07-16 05:54Update twitterapiaccount.py
- Pull request#3SUBHADIPMAITI-DEV2024-07-16 05:54
- Pull request#2SUBHADIPMAITI-DEV2023-11-29 04:43
- Pull request#2SUBHADIPMAITI-DEV2023-11-29 04:42
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 15 stars here means stars gained during the window, not the repo's star count.