This repository contains data for the SemEval 2023 Shared Task 12: Sentiment Analysis in African Languages (AfriSenti-SemEval). More information can be found at the: shared task and competition websites.
| No. | Language | Country |
|---|---|---|
| 1 | Algerian Arabic (arq) | Algeria |
| 2 | Amharic (ama) | Ethiopia |
| 3 | Hausa (hau) | Nigeria |
| 4 | Igbo (ibo) | Nigeria |
| 5 | Kinyarwanda (kin) | Rwanda |
| 6 | Moroccan Arabic/Darija (ary) | Morocco |
| 7 | Mozambique Portuguese (pt-MZ) | Mozambique |
| 8 | Nigerian Pidgin (pcm) | Nigeria |
| 9 | Oromo (orm) | Ethiopia |
| 10 | Swahili (swa) | Kenya/Tanzania |
| 11 | Tigrinya (tir) | Ethiopia |
| 12 | Twi (twi) | Ghana |
| 13 | Xithonga (tso) | Mozambique |
| 14 | Yoruba (yor) | Nigeria |
If you have used our dataset, please cite the following four papers: AfriSenti dataset , AfriSenti-SemEval task description paper, NaijaSenti paper, and ASAB paper.
AfriSenti dataset is available on HugginFace or data folder
@inproceedings{muhammad-etal-2023-afrisenti,
title = "{A}fri{S}enti: A {T}witter Sentiment Analysis Benchmark for {A}frican Languages",
author = "Muhammad, Shamsuddeen and
Abdulmumin, Idris and
Ayele, Abinew and
Ousidhoum, Nedjma and
Adelani, David and
Yimam, Seid and
Ahmad, Ibrahim and
Beloucif, Meriem and
Mohammad, Saif and
Ruder, Sebastian and
Hourrane, Oumaima and
Jorge, Alipio and
Brazdil, Pavel and
Ali, Felermino and
David, Davis and
Osei, Salomey and
Shehu-Bello, Bello and
Lawan, Falalu and
Gwadabe, Tajuddeen and
Rutunda, Samuel and
Belay, Tadesse and
Messelle, Wendimu and
Balcha, Hailu and
Chala, Sisay and
Gebremichael, Hagos and
Opoku, Bernard and
Arthur, Stephen",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.emnlp-main.862",
doi = "10.18653/v1/2023.emnlp-main.862",
pages = "13968--13981",
abstract = "Africa is home to over 2,000 languages from over six language families and has the highest linguistic diversity among all continents. This includes 75 languages with at least one million speakers each. Yet, there is little NLP research conducted on African languages. Crucial in enabling such research is the availability of high-quality annotated datasets. In this paper, we introduce AfriSenti, a sentiment analysis benchmark that contains a total of {\textgreater}110,000 tweets in 14 African languages (Amharic, Algerian Arabic, Hausa, Igbo, Kinyarwanda, Moroccan Arabic, Mozambican Portuguese, Nigerian Pidgin, Oromo, Swahili, Tigrinya, Twi, Xitsonga, and Yoruba) from four language families. The tweets were annotated by native speakers and used in the AfriSenti-SemEval shared task (with over 200 participants, see website: https://afrisenti-semeval.github.io). We describe the data collection methodology, annotation process, and the challenges we dealt with when curating each dataset. We further report baseline experiments conducted on the AfriSenti datasets and discuss their usefulness.",
}
@inproceedings{muhammadSemEval2023,
title = {{SemEval-2023 Task 12: Sentiment Analysis for African Languages (AfriSenti-SemEval)}},
author = {Shamsuddeen Hassan Muhammad and Idris Abdulmumin and Seid Muhie Yimam and David Ifeoluwa Adelani and Ibrahim Sa'id Ahmad and Nedjma Ousidhoum and Abinew Ali Ayele and Saif M. Mohammad and Meriem Beloucif and Sebastian Ruder},
booktitle = {Proceedings of the 17th {{International Workshop}} on {{Semantic Evaluation}} ({{SemEval-2023}})},
publisher = {{Association for Computational Linguistics}},
year = {2023}
}
@inproceedings{muhammad-etal-2022-naijasenti,
title = "{N}aija{S}enti: A {N}igerian {T}witter Sentiment Corpus for Multilingual Sentiment Analysis",
author = "Muhammad, Shamsuddeen Hassan and Adelani, David Ifeoluwa and Ruder, Sebastian and Ahmad, Ibrahim Sa{'}id and Abdulmumin, Idris and Bello, Bello Shehu and Choudhury, Monojit and Emezue, Chris Chinenye and Abdullahi, Saheed Salahudeen and Aremu, Anuoluwapo and orge, Al{\'\i}pio and Brazdil, Pavel",
booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
month = jun,
year = "2022",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2022.lrec-1.63",
pages = "590--602",
}
@InProceedings{yimametalcoling2020,
title = "Exploring {A}mharic Sentiment Analysis from Social Media Texts: Building Annotation Tools and Classification Models",
author = "Yimam, Seid Muhie and
Alemayehu, Hizkiel Mitiku and
Ayele, Abinew and
Biemann, Chris",
booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
pages = "1048--1060"
}
We provide the training, dev and test set for each task below.
We provide sentiment lexicon in some languages that may be useful for the task.
See example here
We provide a starter kit for the competition to create a baseline result. You can open the starter kit in Colab Notebook and run the baseline system. The resultant experiment can be submitted to codalab to ensure all submission format is clear. You can then work on your own system towards the competition.
To run the Colab Notebook, fork this repo first and click the badge "open on colab" on the forked version.
- Task A:
- Task B:
This competition recieves generous support of the Lacuna Fund.
Shield:
This work is licensed under a Creative Commons Attribution 4.0 International License.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent