Task-Specific Pre-Training and Cross Lingual Transfer for Sentiment Analysis in Dravidian Code-Switched Languages
Sentiment analysis in Code-Mixed languages has garnered a lot of attention in recent years. It is an important task for social media monitoring and has many applications, as a large chunk of social media data is Code-Mixed. In this paper, we work on the problem of sentiment analysis for Dravidian Code-Switched languages - Tamil-Engish and Malayalam-English, using three different BERT based models. We leverage task-specific pre-training and cross-lingual transfer to improve on previously reported results, with significant improvement for the Tamil-Engish dataset. We also present a multilingual sentiment classification model that has competitive performance on both Tamil-English and Malayalam-English datasets.
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