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This paper describes the system with which we participated in SemEval-2016 Task 4 (Sentiment Analysis in Twitter) and specifically the Message Polarity Classification subtask. Our system is a weighted ensemble of two systems. The first one is based on a previous sentiment analysis system and uses manually crafted features. The second system of our ensemble uses features based on word embeddings. Our ensemble was ranked 5th among 34 teams. The source code of our system is publicly available.

aueb.twitter.sentiment at SemEval-2016 Task 4: A Weighted Ensemble of SVMs for Twitter Sentiment Analysis