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The phenomenon of mixing the vocabulary and syntax of multiple languageswithin the same utterance is called Code-Mixing. This is more evident inmultilingual societies. In this paper, we have developed a system for SemEval2020: Task 9 on Sentiment Analysis for Code-Mixed Social Media Text. Our systemfirst generates two types of embeddings for the social media text. In those,the first one is character level embeddings to encode the character levelinformation and to handle the out-of-vocabulary entries and the second one isFastText word embeddings for capturing morphology and semantics. These twoembeddings were passed to the LSTM network and the system outperformed thebaseline model.

gundapusunil at SemEval-2020 Task 9: Syntactic Semantic LSTM Architecture for SENTIment Analysis of Code-MIXed Data