GitHub repository: K-Divyasri/ACL-Emotional_Analysis
Description: This is a proof of concept for the Emotional Analysis shared task organised by the ACL DravidanLangTech 2022. We converted it into a pandas dataframe and started preprocessing We removed the emoticons and removed unmatched datapoints from the dataframe along with the stop words, we then printed out distribution of the dataframe and found the data was highly imbalanced , so we used 'SMOTE -  Synthetic Oversampling Technique' to balance the data and appplied a LaBSE transformer which is a derivate of the BERT model , we passed it to a SVM classifier attaining an accuracy of 0.44