Sentiment Analysis is an application of Natural Language Processing (NLP) which deals with text classification. This methodology classifies the text into various sentiments e.g., Positive or Negative, Happy, Sad or Neutral. The goal of this technique is to extract the underlying sentiment of a text that has been used in different social media.
active 2023-10-04 → 2023-10-04 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2023-10-04 to 2023-10-04. Pushes: 1 total, peak 1 in a day. Pull requests: 2 total, peak 2 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
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| lbasyal | 3 | 1 | 2 | 0 |
Recent activity
Latest issues, pull requests and releases
- Pull request#4lbasyal2023-10-04 04:46
- Pull request#4lbasyal2023-10-04 04:43
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.