“Motivated by the lack of annotated data specifically tailoring religion and the poor interoperability of current datasets, in this article we propose a fine-grained labeling scheme for religious hate speech detection. Such scheme lies on a wider and highly-interoperable taxonomy of abusive language, and covers the three main monotheistic religions: Judaism, Christianity and Islam. Moreover, we introduce a Twitter dataset in two languages—English and Italian—that has been annotated following the proposed annotation scheme.” https://peerj.com/articles/cs-1128.pdf Share this: Click to share on Facebook (Opens in new window) Facebook Click to share on X (Opens in new window) X Like this:Like Loading... Post navigation EU rights watchdog warns of bias in AI-based detection of crime, hate-speech (Reuters) Hate Speech and Counter Speech Detection: Conversational Context Does Matter (ACL Anthology)