Abstract
As the world around us continues to become increasingly digital, it has been acknowledged that there is a growing need for emotion analysis of social media content. The task of identifying the emotion in a given text has many practical applications ranging from screening public health to business and management. In this paper, we propose a language agnostic model that focuses on emotion analysis in Tamil text. Our experiments yielded an F1-score of 0.010.
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CITATION STYLE
Krithika, S., Divyasri, K., Gayathri, G. L., Thenmozhi, D., Bharathi, B., & Senthilkumar, B. (2022). PANDAS@TamilNLP-ACL2022: Emotion Analysis in Tamil Text using Language Agnostic Embeddings. In DravidianLangTech 2022 - 2nd Workshop on Speech and Language Technologies for Dravidian Languages, Proceedings of the Workshop (pp. 105–111). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.dravidianlangtech-1.17
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