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We describe our approach for the SemEval-2014 task 9: Sentiment Analysis in Twitter. We make use of an ensemble learning method for sentiment classification of tweets that relies on varied features such as feature hashing, part-of-speech, and lexical features. Our system was evaluated in the Twitter message-level task.

Biocom Usp: Tweet Sentiment Analysis with Adaptive Boosting Ensemble