No 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.

No abstract

No abstract

Due to the exponentially increasing reach of social media, it is essential to focus on its negative aspects as it can potentially divide society and incite people into violence. In this paper, we present our system description of work on the shared task ComMA@ICON, where we have to classify how aggressive the sentence is and if the sentence is gender-biased or communal-biased.These three could be the primary reasons to cause significant problems in society. As team Hypers we have proposed an approach which utilizes different pretrained models with Attention and mean pooling methods. We were able to get Rank 3 with 0.223 Instance F1 score on Bengali, Rank 2 with 0.322 Instance F1 score on Multi-lingual set, Rank 4 with 0.129 Instance F1 score on Meitei and Rank 5 with 0.336 Instance F1 score on Hindi. The source code and the pretrained models of this work can be found here 1 .