mlsanityData to 7 Oct 2026

HERDPhobia: A Dataset for Hate Speech against Fulani in Nigeria

arXiv 2211.15262 ↗First posted 28 Nov 2022cs.CLcited by 12

Not on the map. Why?

Abstract (arXiv)

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.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 6 of its 19 references that are in the map. First posted on arXiv 28 Nov 2022.

Builds on

6 of 19 references.

References · 6

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2017Automated Hate Speech Detection and the Problem of Offensive Languagecited by 724
  3. 2019Multilingual and Multi-Aspect Hate Speech Analysiscited by 133
  4. 2021XLM-T: Multilingual Language Models in Twitter for Sentiment Analysis and Beyondcited by 114
  5. 2022NaijaSenti: A Nigerian Twitter Sentiment Corpus for Multilingual Sentiment Analysiscited by 64
  6. 2022yosm: A new yoruba sentiment corpus for movie reviewscited by 14

Built on by

Cited by year

Citing papers per year: 2023: 3; 2024: 5; 2025: 4.

12 papers.