Amobee at SemEval-2017 Task 4: Deep Learning System for Sentiment Detection on Twitter

05/03/2017

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by   Alon Rozental, et al.

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This paper describes the Amobee sentiment analysis system, adapted to compete in SemEval 2017 task 4. The system consists of two parts: a supervised training of RNN models based on a Twitter sentiment treebank, and the use of feedforward NN, Naive Bayes and logistic regression classifiers to produce predictions for the different sub-tasks. The algorithm reached the 3rd place on the 5-label classification task (sub-task C).