  This paper 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. The proposed system obtained 0.69
(best run) in terms of F1 score on the given test data and achieved the 9th
place (Codalab username: somban) in the SentiMix Hindi-English subtask.
