Bits2020@ Dravidian-CodeMix-FIRE2020: Sub-Word Level Sentiment Analysis of Dravidian Code Mixed Data

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.