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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 61–70 of 73 papers

TitleStatusHype
Enriching Abusive Language Detection with Community Context—0
Evaluating Performance of an Adult Pornography Classifier for Child Sexual Abuse Detection—0
Generalisability of Topic Models in Cross-corpora Abusive Language Detection—0
Graph-based Features for Automatic Online Abuse Detection—0
Identifying Adversarial Attacks on Text Classifiers—0
Impact Of Content Features For Automatic Online Abuse Detection—0
Improving Generalizability in Implicitly Abusive Language Detection with Concept Activation Vectors—0
Joint Modelling of Emotion and Abusive Language Detection—0
Language Identification and Named Entity Recognition in Hinglish Code Mixed Tweets—0
LIIR at SemEval-2020 Task 12: A Cross-Lingual Augmentation Approach for Multilingual Offensive Language Identification—0
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