Hate Speech and Cyberbullying Detection
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Scope of this subject
This cluster of papers focuses on the automated detection of hate speech, offensive language, and cyberbullying in social media platforms such as Twitter. It explores various techniques including machine learning, natural language processing, and deep learning to identify and categorize abusive content, with a specific emphasis on mitigating online harassment and promoting online safety.
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Research vocabulary
hate speech detection; cyberbullying detection; offensive language detection; online hate speech; offensive language; multilingual text classification; social media content moderation; online abuse; harmful content detection; toxicity detection; automated content moderation; social media abuse; online toxicity; toxic comment detection; abusive language; online content moderation; online hate; misogyny detection; sexism detection; offensive content detection; counterspeech; code-mixed text; social media safety; toxic comments; toxic language detection
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No owner-reviewed answer has been published for this exact subject page. This is a gap in this collection; it does not establish that the answer is unavailable elsewhere.
Numeric address and provenance
Morton address: 36183591008472275 · morton4x16-v1
Coordinates: (3, 17, 1702, 12262). The address interleaves categorical identifier bits. Nearby addresses are not guaranteed to describe semantically similar subjects.
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