Abstract:
This paper presents the methodologies implemented while classifying Dravidian code-mixed comments
according to their polarity in the evaluation of the track ‘Sentiment Analysis for Davidian Languages in
Code-Mixed Text’ proposed by Forum of Information Retrieval Evaluation in 2020. The implemented
method used a sub-word level representation to capture the sentiment of the text. Using a Long Short
Term Memory (LSTM) network along with language-specific preprocessing, the model classified the text
according to its polarity. With F1-scores of 0.61 and 0.60, the model achieved an overall rank of 5 and 12
in the Tamil and Malayalam tasks respectively.