Optimize_Prime@DravidianLangTech-ACL2022: Emotion Analysis in Tamil

• URL: http://arxiv.org/abs/2204.09087v1
• Date: Tue, 19 Apr 2022 18:47:18 GMT
• Title: Optimize_Prime@DravidianLangTech-ACL2022: Emotion Analysis in Tamil
• Authors: Omkar Gokhale, Shantanu Patankar, Onkar Litake, Aditya Mandke, Dipali Kadam
• Abstract summary: This paper aims to perform an emotion analysis of social media comments in Tamil. The task aimed to classify social media comments into categories of emotion like Joy, Anger, Trust, Disgust, etc.
• Score: 1.0066310107046081
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: This paper aims to perform an emotion analysis of social media comments in Tamil. Emotion analysis is the process of identifying the emotional context of the text. In this paper, we present the findings obtained by Team Optimize_Prime in the ACL 2022 shared task "Emotion Analysis in Tamil." The task aimed to classify social media comments into categories of emotion like Joy, Anger, Trust, Disgust, etc. The task was further divided into two subtasks, one with 11 broad categories of emotions and the other with 31 specific categories of emotion. We implemented three different approaches to tackle this problem: transformer-based models, Recurrent Neural Networks (RNNs), and Ensemble models. XLM-RoBERTa performed the best on the first task with a macro-averaged f1 score of 0.27, while MuRIL provided the best results on the second task with a macro-averaged f1 score of 0.13.

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