Examining temporal bias in abusive language detection

M **, Y Mu, D Maynard, K Bontcheva - arxiv preprint arxiv:2309.14146, 2023 - arxiv.org
The use of abusive language online has become an increasingly pervasive problem that
damages both individuals and society, with effects ranging from psychological harm right …

hate-alert@ dravidianlangtech: Multimodal abusive language detection and sentiment analysis in dravidian languages

S Barman, M Das - Proceedings of the Third Workshop on Speech …, 2023 - aclanthology.org
The use of abusive language on social media platforms is a prevalent issue that requires
effective detection. Researchers actively engage in abusive language detection and …

hate-alert@ LT-EDI-2023: Hope Speech Detection Using Transformer-Based Models

M Das, S Barman, S Chatterjee - Proceedings of the Third …, 2023 - aclanthology.org
Social media platforms have become integral to our daily lives, facilitating instant sharing of
thoughts and ideas. While these platforms often host inspiring, motivational, and positive …

Toxic Memes: A Survey of Computational Perspectives on the Detection and Explanation of Meme Toxicities

DSM Pandiani, ETK Sang, D Ceolin - arxiv preprint arxiv:2406.07353, 2024 - arxiv.org
Internet memes, channels for humor, social commentary, and cultural expression, are
increasingly used to spread toxic messages. Studies on the computational analyses of toxic …

Attribute-enhanced Selection of Proper Demonstrations for Harmful Meme Detection

M Lin, Q Huang, Q Lu, X Guo… - 2024 27th International …, 2024 - ieeexplore.ieee.org
Internet memes are becoming increasingly prevalent across social media platforms, but also
leveraged by malicious users to spread harmful speech. Recent studies have achieved …