  Social media platforms allow users to freely share their opinions about
issues or anything they feel like. However, they also make it easier to spread
hate and abusive content. The Fulani ethnic group has been the victim of this
unfortunate phenomenon. This paper introduces the HERDPhobia - the first
annotated hate speech dataset on Fulani herders in Nigeria - in three
languages: English, Nigerian-Pidgin, and Hausa. We present a benchmark
experiment using pre-trained languages models to classify the tweets as either
hateful or non-hateful. Our experiment shows that the XML-T model provides
better performance with 99.83% weighted F1. We released the dataset at
https://github.com/hausanlp/HERDPhobia for further research.
