Comparative Studies of Detecting Abusive Language on Twitter

Younghun Lee
Younghun Lee

arXiv: Computation and Language, Volume abs/1808.10245, 2018, Pages 101-106.

Cited by: 0|Bibtex|Views7|DOI:https://doi.org/10.18653/v1/w18-5113
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

The context-dependent nature of online aggression makes annotating large collections of data extremely difficult. Previously studied datasets in abusive language detection have been insufficient in size to efficiently train deep learning models. Recently, Hate and Abusive Speech on Twitter, a dataset much greater in size and reliability, ...More

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