joshzwiebel/Tweet-Sentiment-Extraction

A repository detailing work involved in the kaggle competition Tweet Sentiment Extraction (Jupyter Notebook)

27
/ 100
Experimental

This project helps social media analysts and marketers pinpoint the exact words within a tweet that convey a specific sentiment. It takes raw tweet text and a general sentiment label (like 'positive' or 'negative') as input, and outputs the most relevant phrase or keywords that express that sentiment. Social media managers, brand strategists, and public relations professionals can use this to understand public perception more precisely.

No commits in the last 6 months.

Use this if you need to extract the specific text snippets from tweets that indicate positive, negative, or neutral sentiment.

Not ideal if you are looking to generate new sentiment-aligned text or perform broad topic modeling beyond sentiment.

social-media-analytics brand-monitoring public-relations customer-feedback sentiment-analysis
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 8 / 25
Community 15 / 25

How are scores calculated?

Stars

7

Forks

4

Language

Jupyter Notebook

License

Last pushed

Dec 08, 2022

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/nlp/joshzwiebel/Tweet-Sentiment-Extraction"

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