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HERDPhobia: A Dataset for Hate Speech against Fulani in Nigeria

2022-11-28 12:30:11
Saminu Mohammad Aliyu, Gregory Maksha Wajiga, Muhammad Murtala, Shamsuddeen Hassan Muhammad, Idris Abdulmumin, Ibrahim Said Ahmad
arXiv_CL
   
Abstract

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 this https URL for further research.

Abstract (translated)

URL

https://arxiv.org/abs/2211.15262

PDF

https://arxiv.org/pdf/2211.15262.pdf

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