@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.",
}
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<abstract>We present the first Africentric SemEval Shared task, Sentiment Analysis for African Languages (AfriSenti-SemEval) - The dataset is available at 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.</abstract>
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%0 Conference Proceedings
%T SemEval-2023 Task 12: Sentiment Analysis for African Languages (AfriSenti-SemEval)
%A Muhammad, Shamsuddeen Hassan
%A Abdulmumin, Idris
%A Yimam, Seid Muhie
%A Adelani, David Ifeoluwa
%A Ahmad, Ibrahim Said
%A Ousidhoum, Nedjma
%A Ayele, Abinew Ali
%A Mohammad, Saif
%A Beloucif, Meriem
%A Ruder, Sebastian
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Da San Martino, Giovanni
%Y Tayyar Madabushi, Harish
%Y Kumar, Ritesh
%Y Sartori, Elisa
%S Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F muhammad-etal-2023-semeval
%X We present the first Africentric SemEval Shared task, Sentiment Analysis for African Languages (AfriSenti-SemEval) - The dataset is available at 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.
%R 10.18653/v1/2023.semeval-1.315
%U https://aclanthology.org/2023.semeval-1.315
%U https://doi.org/10.18653/v1/2023.semeval-1.315
%P 2319-2337
Markdown (Informal)
[SemEval-2023 Task 12: Sentiment Analysis for African Languages (AfriSenti-SemEval)](https://aclanthology.org/2023.semeval-1.315) (Muhammad et al., SemEval 2023)
ACL
- Shamsuddeen Hassan Muhammad, Idris Abdulmumin, Seid Muhie Yimam, David Ifeoluwa Adelani, Ibrahim Said Ahmad, Nedjma Ousidhoum, Abinew Ali Ayele, Saif Mohammad, Meriem Beloucif, and Sebastian Ruder. 2023. SemEval-2023 Task 12: Sentiment Analysis for African Languages (AfriSenti-SemEval). In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 2319–2337, Toronto, Canada. Association for Computational Linguistics.