This paper describes the submission of team IIP in SemEval-2016 Task 4 Subtask A. The presented system is a novel weighted sum ensemble approach for sentiment analysis of short informal texts. The ensemble combines member classifiers that output classification confidence metrics. For the ensemble classification decision the members are combined by weights. In the presented approach the weights are derived to prioritize specific classes in multi-class classification. The presented results confirm that this improves results for the prioritized classes. The official task submission achieved a macro-averaged negative positive F1 of 57.4%. Post submission changes resulted in a Fl score of 60.2%. The evaluation also shows that the system outperforms other ensemble methods.
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