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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

Showing 5160 of 73 papers

TitleStatusHype
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 Networks0
Offensive Language Analysis using Deep Learning ArchitectureCode0
Conversational Networks for Automatic Online Moderation0
Did you offend me? Classification of Offensive Tweets in Hinglish LanguageCode0
Determining Code Words in Euphemistic Hate Speech Using Word Embedding Networks0
Aggressive language in an online hacking forum0
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