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HausaHate: An Expert Annotated Corpus for Hausa Hate Speech Detection

Domain:

natural language processing

Record type:

dataset
Creator:
AssAbdulmumin, IdrisAhmad, Ibrahim SaidAlv
Publisher:
Und
Host:avatar
We introduce the first expert annotated corpus of Facebook comments for Hausa hate speech detection. The corpus titled HausaHate comprises 2,000 comments extracted from Western African Facebook pages and manually annotated by three Hausa native speakers, who are also NLP experts. Our corpus was annotated using two different layers. We first labeled each comment according to a binary classification: offensive versus non-offensive. Then, offensive comments were also labeled according to hate speech targets: race, gender and none. Lastly, a baseline model using fine-tuned LLM for Hausa hate speech detection is presented, highlighting the challenges of hate speech detection tasks for indigenous languages in Africa, as well as future advances.

Visit

doi.orgunderline.io

Tasks

hate speech detectiontext classification

Languages

Hausa

Tags

Computational LinguisticsNatural Language ProcessingArtificial Intelligence

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