#Code-Mixed Sentiment Analysis
This work describes the participation of LIMSI_UPV team in SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text. The proposed approach competed in SentiMix Hindi-English subtask, that addresses the problem of predicting the sentiment of a given Hindi-English code-mixed tweet. We propose Recurrent Convolutional Neural Network that combines both the recurrent neural network and the convolutional network to better capture the semantics of the text, for code-mixed sentiment analysis.
Download link of the paper: https://arxiv.org/abs/2008.13173
If you use this code please cite our paper:
Somnath Banerjee, Sahar Ghannay, Sophie Rosset, Anne Vilnat and Paolo Rosso. "LIMSI_UPV at SemEval-2020 Task 9: Recurrent Convolutional Neural Network for Code-mixed Sentiment Analysis". Proceedings of the 14th International Workshop on Semantic Evaluation (SemEval-2020), Association for Computational Linguistics, 2020, December, Barcelona, Spain.
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