Abuse Detection
30 papers with code • 0 benchmarks • 4 datasets
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).
Benchmarks
These leaderboards are used to track progress in Abuse Detection
Hate Speech and Offensive Language
Most implemented papers
Online abuse detection: the value of preprocessing and neural attention models
ddhruvkr/Online_Abuse_Detection
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WS 2019
We propose an attention-based neural network approach to detect abusive speech in online social networks.
Multi-label Hate Speech and Abusive Language Detection in Indonesian Twitter
Hate speech and abusive language spreading on social media need to be detected automatically to avoid conflict between citizen.
Pay ``Attention'' to your Context when Classifying Abusive Language
The goal of any social media platform is to facilitate healthy and meaningful interactions among its users.
Challenges and frontiers in abusive content detection
Online abusive content detection is an inherently difficult task.
HateMonitors: Language Agnostic Abuse Detection in Social Media
punyajoy/HateMonitors-HASOC
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In this paper, we present our machine learning model, HateMonitor, developed for Hate Speech and Offensive Content Identification in Indo-European Languages (HASOC), a shared task at FIRE 2019.
WAC: A Corpus of Wikipedia Conversations for Online Abuse Detection
This large corpus of more than 380k annotated messages opens perspectives for online abuse detection and especially for context-based approaches.
Kungfupanda at SemEval-2020 Task 12: BERT-Based Multi-Task Learning for Offensive Language Detection
wenliangdai/multi-task-offensive-language-detection
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Nowadays, offensive content in social media has become a serious problem, and automatically detecting offensive language is an essential task.
Multimodal Meme Dataset (MultiOFF) for Identifying Offensive Content in Image and Text
Since there was no publicly available dataset for multimodal offensive meme content detection, we leveraged the memes related to the 2016 U. S. presidential election and created the MultiOFF multimodal meme dataset for offensive content detection dataset.
Intersectional Bias in Hate Speech and Abusive Language Datasets
Algorithms are widely applied to detect hate speech and abusive language in social media.
Evaluating Performance of an Adult Pornography Classifier for Child Sexual Abuse Detection
The information technology revolution has facilitated reaching pornographic material for everyone, including minors who are the most vulnerable in case they were abused.
