The “Sentiment Analysis for Code-Mixed Social Media Text” task at the SemEval 2020 competition focuses on sentiment analysis in code-mixed social media text , specifically, on the combination of English with Spanish (Spanglish) and Hindi (Hinglish). In this paper, we present a system able to classify tweets, from Spanish and English languages, into positive, negative and neutral. Firstly, we built a classifier able to provide corresponding sentiment labels. Besides the sentiment labels, we provide the language labels at the word level. Secondly, we generate a word-level representation, using Convolutional Neural Network (CNN) architecture. Our solution indicates promising results for the Sentimix Spanglish-English task (0.744), the team, Lavinia_Ap, occupied the 9th place. However, for the Sentimix Hindi-English task (0.324) the results have to be improved.