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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 2650 of 73 papers

TitleStatusHype
A Unified Deep Learning Architecture for Abuse Detection0
CoLLAB: A Collaborative Approach for Multilingual Abuse Detection0
Enriching Abusive Language Detection with Community Context0
Generalisability of Topic Models in Cross-corpora Abusive Language Detection0
Graph-based Features for Automatic Online Abuse Detection0
Identifying Adversarial Attacks on Text Classifiers0
Impact Of Content Features For Automatic Online Abuse Detection0
Improving Generalizability in Implicitly Abusive Language Detection with Concept Activation Vectors0
Joint Modelling of Emotion and Abusive Language Detection0
Language Identification and Named Entity Recognition in Hinglish Code Mixed Tweets0
LIIR at SemEval-2020 Task 12: A Cross-Lingual Augmentation Approach for Multilingual Offensive Language Identification0
Machine Generated Text: A Comprehensive Survey of Threat Models and Detection Methods0
Mind Your Language: Abuse and Offense Detection for Code-Switched Languages0
Multilingual and Multimodal Abuse Detection0
Neural Character-based Composition Models for Abuse Detection0
Overview of the 2023 ICON Shared Task on Gendered Abuse Detection in Indic Languages0
Predictive Response Optimization: Using Reinforcement Learning to Fight Online Social Network Abuse0
Stereotypical Bias Removal for Hate Speech Detection Task using Knowledge-based Generalizations0
Tackling Online Abuse: A Survey of Automated Abuse Detection Methods0
The Online Behaviour of the Algerian Abusers in Social Media Networks0
Modeling Users and Online Communities for Abuse Detection: A Position on Ethics and Explainability0
Throttling Poisson Processes0
Toxicity Detection for Indic Multilingual Social Media Content0
UoB at SemEval-2020 Task 12: Boosting BERT with Corpus Level Information0
Voucher Abuse Detection with Prompt-based Fine-tuning on Graph Neural Networks0
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