AbhishekC20001/Sentiment-Analysis-for-COVID-Vaccines-

Fetched real-time data from Twitter API and performed data cleaning and preprocessing. Made use of NLP techniques such as tokenization, stemming, and tf-idf vectorization. Using the K-Means Clustering algorithm, the tweets were classified into 3 sentiments and the analysis report consisting of charts was displayed using Flask.

18
/ 100
Experimental

No commits in the last 6 months.

No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 3 / 25
Maturity 1 / 25
Community 14 / 25

How are scores calculated?

Stars

4

Forks

3

Language

Jupyter Notebook

License

Last pushed

Jun 22, 2021

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/nlp/AbhishekC20001/Sentiment-Analysis-for-COVID-Vaccines-"

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