To date, athletes were not observed as a vulnerable group, so they were not a subject of automatic Hate Speech detection and recognition from content published on Social Media. This paper explores whether a model trained on the dataset from one Social Media and not related to any specific domain can be efficient for the Hate Speech binary classification of test sets regarding the sports domain. The experiments deal with Hate Speech detection in Serbian. BiLSTM deep neural network was learned with different parameters, and the results showed high Precision of detecting Hate Speech in sports domain (96% and 97%) and pretty low Recall.https://journalofbigdata.springeropen.com/articles/10.1186/s40537-023-00766-9Share this:FacebookXLike this:Like Loading... Post navigation Addressing hate speech through education: a guide for policy-makers (UNESCO) Online Hate and Harassment: The American Experience 2023 (ADL)