Towards Sub-Word Level Compositions for Sentiment Analysis of Hindi-English Code Mixed Text

Understand

Sentiment analysis (SA) using code-mixed data from social media has several applications in opinion mining ranging from customer satisfaction to social campaign analysis in multilingual societies.

• Advances in this area are impeded by the lack of a suitable annotated dataset.
• We introduce a Hindi-English (Hi-En) code-mixed dataset for sentiment analysis and perform empirical analysis comparing the suitability and performance of various state-of-the-art SA methods in social media.
• In this paper, we introduce learning sub-word level representations in LSTM (Subword-LSTM) architecture instead of character-level or word-level representations.