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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

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Showing 1–50 of 73 papers

TitleStatusHype
ConvAbuse: Data, Analysis, and Benchmarks for Nuanced Abuse Detection in Conversational AICode1
One-step and Two-step Classification for Abusive Language Detection on TwitterCode1
Entropy-based Attention Regularization Frees Unintended Bias Mitigation from ListsCode1
AbuseAnalyzer: Abuse Detection, Severity and Target Prediction for Gab PostsCode1
Kungfupanda at SemEval-2020 Task 12: BERT-Based Multi-Task Learning for Offensive Language DetectionCode1
Intersectional Bias in Hate Speech and Abusive Language DatasetsCode1
Multimodal Meme Dataset (MultiOFF) for Identifying Offensive Content in Image and TextCode1
Comparative Studies of Detecting Abusive Language on TwitterCode1
KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social MediaCode1
Racial Bias in Hate Speech and Abusive Language Detection DatasetsCode0
HateMonitors: Language Agnostic Abuse Detection in Social MediaCode0
HP-BERT: A framework for longitudinal study of Hinduphobia on social media via LLMsCode0
TCAB: A Large-Scale Text Classification Attack BenchmarkCode0
ADIMA: Abuse Detection In Multilingual AudioCode0
Detecting Offensive Language in Tweets Using Deep LearningCode0
Towards Cross-Lingual Audio Abuse Detection in Low-Resource Settings with Few-Shot LearningCode0
Improving Generalizability in Implicitly Abusive Language Detection with Concept Activation VectorsCode0
Offensive Language Analysis using Deep Learning ArchitectureCode0
UM-IU@LING at SemEval-2019 Task 6: Identifying Offensive Tweets Using BERT and SVMsCode0
Understanding Abuse: A Typology of Abusive Language Detection SubtasksCode0
Abusive Language Detection in Online Conversations by Combining Content-and Graph-based FeaturesCode0
WAC: A Corpus of Wikipedia Conversations for Online Abuse DetectionCode0
AAA: Fair Evaluation for Abuse Detection Systems WantedCode0
Did you offend me? Classification of Offensive Tweets in Hinglish LanguageCode0
Multi-label Hate Speech and Abusive Language Detection in Indonesian TwitterCode0
Author Profiling for Abuse DetectionCode0
Explainable Abuse Detection as Intent Classification and Slot FillingCode0
Online abuse detection: the value of preprocessing and neural attention modelsCode0
Breaking the Silence Detecting and Mitigating Gendered Abuse in Hindi, Tamil, and Indian English Online SpacesCode0
Pay ``Attention'' to your Context when Classifying Abusive LanguageCode0
Challenges and frontiers in abusive content detectionCode0
Neural Character-based Composition Models for Abuse Detection—0
Overview of the 2023 ICON Shared Task on Gendered Abuse Detection in Indic Languages—0
Predictive Response Optimization: Using Reinforcement Learning to Fight Online Social Network Abuse—0
Stereotypical Bias Removal for Hate Speech Detection Task using Knowledge-based Generalizations—0
Tackling Online Abuse: A Survey of Automated Abuse Detection Methods—0
The Online Behaviour of the Algerian Abusers in Social Media Networks—0
Modeling Users and Online Communities for Abuse Detection: A Position on Ethics and Explainability—0
Throttling Poisson Processes—0
Toxicity Detection for Indic Multilingual Social Media Content—0
UoB at SemEval-2020 Task 12: Boosting BERT with Corpus Level Information—0
Voucher Abuse Detection with Prompt-based Fine-tuning on Graph Neural Networks—0
What Models Know About Their Attackers: Deriving Attacker Information From Latent Representations—0
Abuse and Fraud Detection in Streaming Services Using Heuristic-Aware Machine Learning—0
Abusive Language Detection with Graph Convolutional Networks—0
Adversarial Robustness for Tabular Data through Cost and Utility Awareness—0
Aggressive language in an online hacking forum—0
A Large-Scale English Multi-Label Twitter Dataset for Cyberbullying and Online Abuse Detection—0
A survey of textual cyber abuse detection using cutting-edge language models and large language models—0
A Unified Deep Learning Architecture for Abuse Detection—0
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