@inproceedings{muhammad-etal-2023-semeval,
    title = "{S}em{E}val-2023 Task 12: Sentiment Analysis for {A}frican Languages ({A}fri{S}enti-{S}em{E}val)",
    author = "Muhammad, Shamsuddeen Hassan  and
      Abdulmumin, Idris  and
      Yimam, Seid Muhie  and
      Adelani, David Ifeoluwa  and
      Ahmad, Ibrahim Said  and
      Ousidhoum, Nedjma  and
      Ayele, Abinew Ali  and
      Mohammad, Saif  and
      Beloucif, Meriem  and
      Ruder, Sebastian",
    editor = {Ojha, Atul Kr.  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Da San Martino, Giovanni  and
      Tayyar Madabushi, Harish  and
      Kumar, Ritesh  and
      Sartori, Elisa},
    booktitle = "Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.semeval-1.315",
    doi = "10.18653/v1/2023.semeval-1.315",
    pages = "2319--2337",
    abstract = "We present the first Africentric SemEval Shared task, Sentiment Analysis for African Languages (AfriSenti-SemEval) - The dataset is available at \url{https://github.com/afrisenti-semeval/afrisent-semeval-2023}. AfriSenti-SemEval is a sentiment classification challenge in 14 African languages: Amharic, Algerian Arabic, Hausa, Igbo, Kinyarwanda, Moroccan Arabic, Mozambican Portuguese, Nigerian Pidgin, Oromo, Swahili, Tigrinya, Twi, Xitsonga, and Yorb (Muhammad et al., 2023), using data labeled with 3 sentiment classes. We present three subtasks: (1) Task A: monolingual classification, which received 44 submissions; (2) Task B: multilingual classification, which received 32 submissions; and (3) Task C: zero-shot classification, which received 34 submissions. The best performance for tasks A and B was achieved by NLNDE team with 71.31 and 75.06 weighted F1, respectively. UCAS-IIE-NLP achieved the best average score for task C with 58.15 weighted F1. We describe the various approaches adopted by the top 10 systems and their approaches.",
}

We present the first Africentric SemEval Shared task, Sentiment Analysis for African Languages (AfriSenti-SemEval) - The dataset is available at \url{https://github.com/afrisenti-semeval/afrisent-semeval-2023}. AfriSenti-SemEval is a sentiment classification challenge in 14 African languages: Amharic, Algerian Arabic, Hausa, Igbo, Kinyarwanda, Moroccan Arabic, Mozambican Portuguese, Nigerian Pidgin, Oromo, Swahili, Tigrinya, Twi, Xitsonga, and Yorb (Muhammad et al., 2023), using data labeled with 3 sentiment classes. We present three subtasks: (1) Task A: monolingual classification, which received 44 submissions; (2) Task B: multilingual classification, which received 32 submissions; and (3) Task C: zero-shot classification, which received 34 submissions. The best performance for tasks A and B was achieved by NLNDE team with 71.31 and 75.06 weighted F1, respectively. UCAS-IIE-NLP achieved the best average score for task C with 58.15 weighted F1. We describe the various approaches adopted by the top 10 systems and their approaches.
Muhammad, Shamsuddeen Hassan Abdulmumin, Idris Yimam, Seid Muhie Adelani, David Ifeoluwa Ahmad, Ibrahim Said Ousidhoum, Nedjma Ayele, Abinew Ali Mohammad, Saif Beloucif, Meriem Ruder, Sebastian
SemEval-2023 Task 12: Sentiment Analysis for African Languages (AfriSenti-SemEval)