“The results indicate that the attention-based models profoundly confuse hate speech with offensive and normal language. However, the pre-trained models outperform state-of-the-art results in terms of accurately predicting the hateful instances.” https://aclanthology.org/2020.alw-1.3.pdf Share this: Click to print (Opens in new window) Print Click to share on Facebook (Opens in new window) Facebook Click to share on LinkedIn (Opens in new window) LinkedIn Click to share on Reddit (Opens in new window) Reddit Click to share on WhatsApp (Opens in new window) WhatsApp Click to share on Bluesky (Opens in new window) Bluesky Click to email a link to a friend (Opens in new window) Email Like this:Like Loading... Post navigation HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection (AAAI) Automatic Detection of Cyberbullying and Abusive Language in Arabic Content on Social Networks: A Survey (Elsevier)