  This paper describes our multi-view ensemble approach to SemEval-2017 Task 4
on Sentiment Analysis in Twitter, specifically, the Message Polarity
Classification subtask for English (subtask A). Our system is a voting
ensemble, where each base classifier is trained in a different feature space.
The first space is a bag-of-words model and has a Linear SVM as base
classifier. The second and third spaces are two different strategies of
combining word embeddings to represent sentences and use a Linear SVM and a
Logistic Regressor as base classifiers. The proposed system was ranked 18th out
of 38 systems considering F1 score and 20th considering recall.
