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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
TCAB: A Large-Scale Text Classification Attack BenchmarkCode0
Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods0
Explainable Abuse Detection as Intent Classification and Slot FillingCode0
Adversarial Robustness for Tabular Data through Cost and Utility Awareness0
Enriching Abusive Language Detection with Community Context0
DE-ABUSE@TamilNLP-ACL 2022: Transliteration as Data Augmentation for Abuse Detection in Tamil0
Darkness can not drive out darkness: Investigating Bias in Hate SpeechDetection Models0
Improving Generalizability in Implicitly Abusive Language Detection with Concept Activation VectorsCode0
Multilingual and Multimodal Abuse Detection0
The Online Behaviour of the Algerian Abusers in Social Media Networks0
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