richouzo/hate-speech-detection-survey

Trained Neural Networks (LSTM, HybridCNN/LSTM, PyramidCNN, Transformers, etc.) & comparison for the task of Hate Speech Detection on the OLID Dataset (Tweets).

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Emerging

This project offers a comparative study of different machine learning models for identifying hate speech in social media posts. It takes English tweets as input and determines whether they contain offensive or hateful language. Social media managers, content moderators, or platform safety teams can use this to understand the effectiveness of various algorithms in detecting harmful content.

No commits in the last 6 months.

Use this if you need to evaluate and compare different advanced natural language processing methods for automatically identifying hate speech in user-generated text, particularly on platforms like Twitter.

Not ideal if you are looking for a ready-to-deploy, out-of-the-box hate speech detection tool without the need for model comparison or research.

content-moderation social-media-management online-safety natural-language-processing harmful-content-detection
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 11 / 25

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21

Forks

3

Language

Jupyter Notebook

License

CC0-1.0

Last pushed

Dec 14, 2021

Commits (30d)

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