“This study investigates offensive and hate speech on Arab social media to build an accurate offensive and hate speech detection system. More precisely, we develop a classification system for determining offensive and hate speech using a multi-task learning (MTL) model built on top of a pre-trained Arabic language model. We train the MTL model on the same task using cross-corpora representing a variation in the offensive and hate context to learn global and dataset-specific contextual representations. The developed MTL model showed a significant performance and outperformed existing models in the literature on three out of four datasets for Arabic offensive and hate speech detection tasks.” https://www.mdpi.com/2227-9709/8/4/69/pdf Share this: Print (Opens in new window) Print Share on Facebook (Opens in new window) Facebook Share on LinkedIn (Opens in new window) LinkedIn Share on Reddit (Opens in new window) Reddit Share on WhatsApp (Opens in new window) WhatsApp Share on Bluesky (Opens in new window) Bluesky Email a link to a friend (Opens in new window) Email Like this:Like Loading... Post navigation Latent Hatred: A Benchmark for Understanding Implicit Hate Speech (Association for Computational Linguistics) A Feature Extraction based Model for Hate Speech Identification (arXiv)