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We present a novel method for determining sentiment intensity. The main goal is to assign a phrase a score from 0 to 1 which indicates the strength of its association with positive sentiment. The proposed model uses a rich set of features with Gaussian processes regression model that computes the final score. The system was evaluated on the data from 7th task of SemEval 2016. Our regression model trained on the development data reached Kendall rank correlation of 0.659 on general English phrases and 0.414 on English Twitter test data.

UWB at SemEval-2016 Task 7: Novel Method for Automatic Sentiment Intensity Determination