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.
HERDPhobia: A Dataset for Hate Speech against Fulani in Nigeria
A hate speech dataset and benchmark experiment classify tweets about Fulani herders in Nigeria using pre-trained language models, with XML-T achieving high F1 performance.
- Year
- 2022
- Venue
- arXiv 2022
- Authors
- 6
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- Abstract onlyARXIV-DEFAULT
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- arxiv.org/abs/2211.15262ARXIV-DEFAULT
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