  Code-switching is a phenomenon in which two or more languages are used in the
same message. Nowadays, it is quite common to find messages with languages
mixed in social media. This phenomenon presents a challenge for sentiment
analysis. In this paper, we use a standard convolutional neural network model
to predict the sentiment of tweets in a blend of Spanish and English languages.
Our simple approach achieved a F1-score of 0.71 on test set on the competition.
We analyze our best model capabilities and perform error analysis to expose
important difficulties for classifying sentiment in a code-switching setting.
