“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/pdfShare this:FacebookXLike 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)