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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 2130 of 73 papers

TitleStatusHype
HateMonitors: Language Agnostic Abuse Detection in Social MediaCode0
Evaluating Performance of an Adult Pornography Classifier for Child Sexual Abuse DetectionCode0
Detecting Offensive Language in Tweets Using Deep LearningCode0
Author Profiling for Abuse DetectionCode0
Breaking the Silence Detecting and Mitigating Gendered Abuse in Hindi, Tamil, and Indian English Online SpacesCode0
Online abuse detection: the value of preprocessing and neural attention modelsCode0
Did you offend me? Classification of Offensive Tweets in Hinglish LanguageCode0
Challenges and frontiers in abusive content detectionCode0
HP-BERT: A framework for longitudinal study of Hinduphobia on social media via LLMsCode0
UM-IU@LING at SemEval-2019 Task 6: Identifying Offensive Tweets Using BERT and SVMsCode0
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