Findings of the Shared Task on Emotion Analysis in Tamil

Abstract

This paper presents the overview of the shared task on emotional analysis in Tamil at DravidianLangTech-ACL 2022. This overview paper presents the dataset used in the shared task, task description, the methodologies used by the participants and the evaluation results of the submissions. Emotion analysis in Tamil shared task consists of two sub tasks. Task A aims to categorize the social media comments in Tamil to 11 emotions and Task B aims to categorize the comments into 31 fine-grained emotions. For conducting experiments, training and development datasets were provided to the participants and results are evaluated for the unseen data. In total, we have received around 24 submissions from 13 teams. For evaluating the models, Precision, Recall, micro average metrics are used.

Text emotional analysis in Natural Language Processing

“…Through appropriate model design and data processing techniques, the challenges of CNN processing long and non English texts can be overcome, and the accuracy and robustness of sentiment analysis tasks can be improved. In the future, more complex network structures and more advanced pre training models can be further explored to promote the development of text sentiment analysis [18].…”

“…Firstly, it is necessary to collect a set of seed words that have already been labeled with emotional polarity. These seed words can be obtained from existing emotional dictionaries, manually annotated datasets, or professional knowledge, and should cover multiple fields and different emotional polarities [22]. Using seed vocabulary as a starting point, the emotional vocabulary list can be expanded through various methods.…”