thefirebanks/Ensemble-Learning-for-Tweet-Classification-of-Hate-Speech-and-Offensive-Language

Contains code for a voting classifier that is part of an ensemble learning model for tweet classification (which includes an LSTM, a bayesian model and a proximity model) and a system for weighted voting

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Experimental

This project helps social media analysts, content moderators, or platform safety teams automatically identify hate speech and offensive language in tweets. It takes tweet text as input and classifies it as either hate speech, offensive, or neither, providing a powerful tool for large-scale content review and policy enforcement.

No commits in the last 6 months.

Use this if you need to automatically detect and categorize hate speech and offensive content within Twitter data.

Not ideal if your primary goal is to understand the nuances of non-English hate speech or if you require fine-grained sentiment analysis beyond offensive language detection.

social-media-moderation content-filtering online-safety brand-reputation text-analysis
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 11 / 25

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Language

Python

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Last pushed

May 08, 2018

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