TextSentimentAnalysis and Sentiment_Analysis_NLP

TextSentimentAnalysis
42
Emerging
Sentiment_Analysis_NLP
23
Experimental
Maintenance 0/25
Adoption 7/25
Maturity 16/25
Community 19/25
Maintenance 2/25
Adoption 1/25
Maturity 7/25
Community 13/25
Stars: 32
Forks: 20
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: MIT
Stars: 1
Forks: 2
Downloads: —
Commits (30d): 0
Language: Jupyter Notebook
License: —
Stale 6m No Package No Dependents
No License Stale 6m No Package No Dependents

About TextSentimentAnalysis

khanfarhan10/TextSentimentAnalysis

Text Sentiment Analysis in Python using Natural Language Processing (NLP) for Negative/Positive Content Detection. Deployed on the Cloud using Streamlit on the Heroku Platform.

This tool helps you quickly understand the overall mood or emotional tone of written content. You provide it with text, and it tells you whether the sentiment is generally positive or negative. It's ideal for anyone who needs to gauge public opinion, analyze customer feedback, or understand the emotional impact of written communication.

customer-feedback-analysis social-media-monitoring market-research public-opinion content-analysis

About Sentiment_Analysis_NLP

MohamedTarek1er/Sentiment_Analysis_NLP

Sentiment Analysis using NLP and Machine Learning classification models, deployed with Streamlit.

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