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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 4150 of 73 papers

TitleStatusHype
LIIR at SemEval-2020 Task 12: A Cross-Lingual Augmentation Approach for Multilingual Offensive Language Identification0
Multimodal Meme Dataset (MultiOFF) for Identifying Offensive Content in Image and TextCode1
Kungfupanda at SemEval-2020 Task 12: BERT-Based Multi-Task Learning for Offensive Language DetectionCode1
WAC: A Corpus of Wikipedia Conversations for Online Abuse DetectionCode0
Stereotypical Bias Removal for Hate Speech Detection Task using Knowledge-based Generalizations0
HateMonitors: Language Agnostic Abuse Detection in Social MediaCode0
Tackling Online Abuse: A Survey of Automated Abuse Detection Methods0
Pay ``Attention'' to your Context when Classifying Abusive LanguageCode0
Multi-label Hate Speech and Abusive Language Detection in Indonesian TwitterCode0
Challenges and frontiers in abusive content detectionCode0
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