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The paper describes experiments on sentiment classification of microblog messages using an architecture allowing general machine learning classifiers to be combined either sequentially to form a multi-step classifier, or in parallel, creating an ensemble classifier. The system achieved very competitive results in the shared task on sentiment analysis in Twitter, in particular on non-Twitter social media data, that is, input it was not specifically tailored to.

NTNUSentEval at SemEval-2016 Task 4: Combining General Classifiers for Fast Twitter Sentiment Analysis