rehanraza24/Twitter-Text-Sentiment-Analysis-

Twitter Text Sentiment Analysis (Preprocessing using Spacy)

13
/ 100
Experimental

This project helps social media analysts and marketers understand public opinion from Twitter data. It takes raw tweets and cleans them by removing noise like retweets, hashtags, and special characters. The output is categorized tweets with an assigned sentiment (positive, negative, neutral), helping you gauge public perception of a topic or brand.

No commits in the last 6 months.

Use this if you need to process large volumes of tweet text to extract sentiment or categorize content for market research or brand monitoring.

Not ideal if you're looking for an out-of-the-box application with a graphical interface, as this project consists of programming notebooks.

social-media-analysis market-research brand-monitoring public-opinion text-classification
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 0 / 25

How are scores calculated?

Stars

10

Forks

Language

Jupyter Notebook

License

Last pushed

Jan 10, 2021

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/nlp/rehanraza24/Twitter-Text-Sentiment-Analysis-"

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