In this study we provide a comprehensive empirical evaluation of numerous public datasets commonly employed in automated hate speech classification. Through rigorous empirical analysis, we present compelling evidence that sheds light on the limitations inherent in the current hate speech datasets used in supervised hate speech classification tasks. Furthermore, we offer a range of statistical analyses to elucidate the weaknesses and strengths inherent in these datasets. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4504059 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 An Introduction to Detection of Hate Speech and Offensive Language in Slovak (IEEE) Exploring Intensities of Hate Speech on Social Media: A Case Study on Explaining Multilingual Models with XAI (JKU Visual Data Science Lab)