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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 1–25 of 73 papers

TitleStatusHype
KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social MediaCode1
One-step and Two-step Classification for Abusive Language Detection on TwitterCode1
Multimodal Meme Dataset (MultiOFF) for Identifying Offensive Content in Image and TextCode1
ConvAbuse: Data, Analysis, and Benchmarks for Nuanced Abuse Detection in Conversational AICode1
Comparative Studies of Detecting Abusive Language on TwitterCode1
AbuseAnalyzer: Abuse Detection, Severity and Target Prediction for Gab PostsCode1
Intersectional Bias in Hate Speech and Abusive Language DatasetsCode1
Kungfupanda at SemEval-2020 Task 12: BERT-Based Multi-Task Learning for Offensive Language DetectionCode1
Entropy-based Attention Regularization Frees Unintended Bias Mitigation from ListsCode1
Evaluating Performance of an Adult Pornography Classifier for Child Sexual Abuse Detection—0
Enriching Abusive Language Detection with Community Context—0
Abuse and Fraud Detection in Streaming Services Using Heuristic-Aware Machine Learning—0
Adversarial Robustness for Tabular Data through Cost and Utility Awareness—0
CoLLAB: A Collaborative Approach for Multilingual Abuse Detection—0
DetoxBench: Benchmarking Large Language Models for Multitask Fraud & Abuse Detection—0
Generalisability of Topic Models in Cross-corpora Abusive Language Detection—0
A Unified Deep Learning Architecture for Abuse Detection—0
Creating and Evaluating Code-Mixed Nepali-English and Telugu-English Datasets for Abusive Language Detection Using Traditional and Deep Learning Models—0
Conversational Networks for Automatic Online Moderation—0
A survey of textual cyber abuse detection using cutting-edge language models and large language models—0
Darkness can not drive out darkness: Investigating Bias in Hate SpeechDetection Models—0
DE-ABUSE@TamilNLP-ACL 2022: Transliteration as Data Augmentation for Abuse Detection in Tamil—0
Abusive Language Detection with Graph Convolutional Networks—0
Detection of Children Abuse by Voice and Audio Classification by Short-Time Fourier Transform Machine Learning implemented on Nvidia Edge GPU device—0
Context-Aware Attention for Understanding Twitter Abuse—0
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