DURGESH716/NLP_Twitter_Analysis

Analyzing Tweets of people whether positive or negative through Natural Language Processing (NLP) techniques like Tokenization, etc

19
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Experimental

This tool helps businesses automatically understand the sentiment of customer feedback found in social media posts, product reviews, or tweets. You input raw text data from these sources, and it outputs classifications indicating whether the sentiment expressed is positive or negative. It's designed for marketing analysts, customer service managers, or product managers who need to quickly gauge public opinion or customer satisfaction without manual review.

No commits in the last 6 months.

Use this if you need to quickly categorize large volumes of text-based customer feedback to understand general sentiment trends.

Not ideal if you need nuanced analysis beyond simple positive/negative sentiment or require interpretation of sarcasm and complex emotional tones.

social-listening customer-feedback brand-reputation market-research customer-satisfaction
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 5 / 25

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Stars

16

Forks

1

Language

Python

License

Last pushed

Feb 07, 2023

Commits (30d)

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