Sentiment Analysis on Multilingual Code Mixing Text Using BERT-BASE: participation of IRLab@IIT(BHU) in Dravidian-CodeMix and HASOC tasks of FIRE2020 (original) (raw)

This paper discusses our participation in the “Sentiment Analysis in Dravidian-CodeMix”, DravidianCodeMix and “Hate Speech and Offensive Content Identification in Indo-European Languages”FIRE 2020 tasks of identifying subjective opinions or reactions on a given topic. Several techniques are applied for sentiment analysis including the recent word embeddings-based methods. BERT, Word2Vec, and ELMo are currently among the most promising and ready-to-use word embedding methods that can convert words into meaningful vectors. We used the BERT_BASE model for sentiment classification of Dravidian-CodeMix data and for HASOC task, our team submitted systems for all the two sub-tasks in three languages Hindi, English, and German with BERT-based system. We report our approach and results which are promising.

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