natural-language-processing-13
Hate Speech Detection
3260 papers • 126 benchmarks • 313 datasets
Hate speech detection is the task of detecting if communication such as text, audio, and so on contains hatred and or encourages violence towards a person or a group of people. This is usually based on prejudice against 'protected characteristics' such as their ethnicity, gender, sexual orientation, religion, age et al. Some example benchmarks are ETHOS and HateXplain. Models can be evaluated with metrics like the F-score or F-measure.
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Benchmarks
These leaderboards are used to track progress in hate-speech-detection-26
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Dataset
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Ethos Binary
Ethos Binary
HateXplain
HateXplain
Ethos MultiLabel
Ethos MultiLabel
Libraries
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5 papers 90
