AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages
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| Format: | Preprint |
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2025
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| author | Muhammad, Shamsuddeen Hassan Abdulmumin, Idris Ayele, Abinew Ali Adelani, David Ifeoluwa Ahmad, Ibrahim Said Aliyu, Saminu Mohammad Onyango, Nelson Odhiambo Wanzare, Lilian D. A. Rutunda, Samuel Aliyu, Lukman Jibril Alemneh, Esubalew Hourrane, Oumaima Gebremichael, Hagos Tesfahun Ismail, Elyas Abdi Beloucif, Meriem Jibril, Ebrahim Chekol Bukula, Andiswa Mabuya, Rooweither Osei, Salomey Oppong, Abigail Belay, Tadesse Destaw Guge, Tadesse Kebede Asfaw, Tesfa Tegegne Chukwuneke, Chiamaka Ijeoma Röttger, Paul Yimam, Seid Muhie Ousidhoum, Nedjma |
| author_facet | Muhammad, Shamsuddeen Hassan Abdulmumin, Idris Ayele, Abinew Ali Adelani, David Ifeoluwa Ahmad, Ibrahim Said Aliyu, Saminu Mohammad Onyango, Nelson Odhiambo Wanzare, Lilian D. A. Rutunda, Samuel Aliyu, Lukman Jibril Alemneh, Esubalew Hourrane, Oumaima Gebremichael, Hagos Tesfahun Ismail, Elyas Abdi Beloucif, Meriem Jibril, Ebrahim Chekol Bukula, Andiswa Mabuya, Rooweither Osei, Salomey Oppong, Abigail Belay, Tadesse Destaw Guge, Tadesse Kebede Asfaw, Tesfa Tegegne Chukwuneke, Chiamaka Ijeoma Röttger, Paul Yimam, Seid Muhie Ousidhoum, Nedjma |
| contents | Hate speech and abusive language are global phenomena that need socio-cultural background knowledge to be understood, identified, and moderated. However, in many regions of the Global South, there have been several documented occurrences of (1) absence of moderation and (2) censorship due to the reliance on keyword spotting out of context. Further, high-profile individuals have frequently been at the center of the moderation process, while large and targeted hate speech campaigns against minorities have been overlooked. These limitations are mainly due to the lack of high-quality data in the local languages and the failure to include local communities in the collection, annotation, and moderation processes. To address this issue, we present AfriHate: a multilingual collection of hate speech and abusive language datasets in 15 African languages. Each instance in AfriHate is annotated by native speakers familiar with the local culture. We report the challenges related to the construction of the datasets and present various classification baseline results with and without using LLMs. The datasets, individual annotations, and hate speech and offensive language lexicons are available on https://github.com/AfriHate/AfriHate |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_08284 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages Muhammad, Shamsuddeen Hassan Abdulmumin, Idris Ayele, Abinew Ali Adelani, David Ifeoluwa Ahmad, Ibrahim Said Aliyu, Saminu Mohammad Onyango, Nelson Odhiambo Wanzare, Lilian D. A. Rutunda, Samuel Aliyu, Lukman Jibril Alemneh, Esubalew Hourrane, Oumaima Gebremichael, Hagos Tesfahun Ismail, Elyas Abdi Beloucif, Meriem Jibril, Ebrahim Chekol Bukula, Andiswa Mabuya, Rooweither Osei, Salomey Oppong, Abigail Belay, Tadesse Destaw Guge, Tadesse Kebede Asfaw, Tesfa Tegegne Chukwuneke, Chiamaka Ijeoma Röttger, Paul Yimam, Seid Muhie Ousidhoum, Nedjma Computation and Language Hate speech and abusive language are global phenomena that need socio-cultural background knowledge to be understood, identified, and moderated. However, in many regions of the Global South, there have been several documented occurrences of (1) absence of moderation and (2) censorship due to the reliance on keyword spotting out of context. Further, high-profile individuals have frequently been at the center of the moderation process, while large and targeted hate speech campaigns against minorities have been overlooked. These limitations are mainly due to the lack of high-quality data in the local languages and the failure to include local communities in the collection, annotation, and moderation processes. To address this issue, we present AfriHate: a multilingual collection of hate speech and abusive language datasets in 15 African languages. Each instance in AfriHate is annotated by native speakers familiar with the local culture. We report the challenges related to the construction of the datasets and present various classification baseline results with and without using LLMs. The datasets, individual annotations, and hate speech and offensive language lexicons are available on https://github.com/AfriHate/AfriHate |
| title | AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2501.08284 |