This paper elaborates on our work in designing a system for SemEval 2023 Task 12: AfriSenti-SemEval, which involves sentiment analysis for low-resource African languages using the Twitter dataset. We utilised a pre-trained model to perform sentiment classification in Hausa-language tweets. We used a multilingual version of the roBERTa model, which is pretrained on 100 languages, to classify sentiments in Hausa. To tokenize the text, we used the AfriBERTa model, which is specifically pretrained on African languages.
CITATION STYLE
Ramanathan, N., Sivanaiah, R., Suseelan, A. D., & Thanagathai, M. T. N. (2023). TechSSN at SemEval-2023 Task 12: Monolingual Sentiment Classification in Hausa Tweets. In 17th International Workshop on Semantic Evaluation, SemEval 2023 - Proceedings of the Workshop (pp. 1190–1194). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.semeval-1.165
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