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Abuse Detection

Abuse detection is the task of identifying abusive behaviors, such as hate speech, offensive language, sexism and racism, in utterances from social media platforms (Source: https://arxiv.org/abs/1802.00385).

Papers

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Showing 51–60 of 73 papers

TitleStatusHype
Multi-label Hate Speech and Abusive Language Detection in Indonesian TwitterCode0
Pay ``Attention'' to your Context when Classifying Abusive LanguageCode0
Online abuse detection: the value of preprocessing and neural attention modelsCode0
Racial Bias in Hate Speech and Abusive Language Detection DatasetsCode0
Abusive Language Detection in Online Conversations by Combining Content-and Graph-based FeaturesCode0
UM-IU@LING at SemEval-2019 Task 6: Identifying Offensive Tweets Using BERT and SVMsCode0
Abusive Language Detection with Graph Convolutional Networks—0
Offensive Language Analysis using Deep Learning ArchitectureCode0
Conversational Networks for Automatic Online Moderation—0
Determining Code Words in Euphemistic Hate Speech Using Word Embedding Networks—0
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