sharmaroshan/Twitter-Sentiment-Analysis

It is a Natural Language Processing Problem where Sentiment Analysis is done by Classifying the Positive tweets from negative tweets by machine learning models for classification, text mining, text analysis, data analysis and data visualization

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Established

This project helps social media managers or brand analysts automatically sort through tweets to identify those containing hate speech. It takes raw tweet data as input and categorizes each tweet as either 'racist/sexist' or 'not racist/sexist'. This allows users to quickly flag and address problematic content.

270 stars. No commits in the last 6 months.

Use this if you need to automatically monitor and classify large volumes of tweets for hate speech, specifically racist or sexist content.

Not ideal if you need to detect a broader range of negative sentiments beyond hate speech, or if your primary focus is general customer feedback analysis.

social-media-monitoring brand-reputation content-moderation public-relations social-listening
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

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Stars

270

Forks

128

Language

Jupyter Notebook

License

GPL-3.0

Last pushed

Nov 03, 2023

Commits (30d)

0

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