AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languages
Shamsuddeen Hassan Muhammad, Idris Abdulmumin, Abinew Ali Ayele, Nedjma OUSIDHOUM, David Ifeoluwa Adelani, Seid Muhie Yimam, Ibrahim Said Ahmad, Meriem Beloucif
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 >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.
BibTeX
@inproceedings{
muhammad2023afrisenti,
title={AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languages},
author={Shamsuddeen Hassan Muhammad and Idris Abdulmumin and Abinew Ali Ayele and Nedjma OUSIDHOUM and David Ifeoluwa Adelani and Seid Muhie Yimam and Ibrahim Said Ahmad and Meriem Beloucif and Saif M. Mohammad and Sebastian Ruder and Oumaima Hourrane and Alipio Jorge and Pavel Brazdil and Felermino D. M. A. Ali and Davis David and Salomey Osei and Bello Shehu-Bello and Falalu Ibrahim Lawan and Tajuddeen Gwadabe and Samuel Rutunda and Tadesse Destaw Belay and Wendimu Baye Messelle and Hailu Beshada Balcha and Sisay Adugna Chala and Hagos Tesfahun Gebremichael and Bernard Opoku and Stephen Arthur},
booktitle={The 2023 Conference on Empirical Methods in Natural Language Processing},
year={2023},
url={https://openreview.net/forum?id=7RzRbVXWPN}
}