This paper describes the participation of Amobee in the shared sentiment analysis task at SemEval 2018. We participated in all the English sub-tasks and the Spanish valence tasks. Our system consists of three parts: training task-specific word embeddings, training a model consisting of gated-recurrentunits (GRU) with a convolution neural network (CNN) attention mechanism and training stacking-based ensembles for each of the subtasks. Our algorithm reached 3rd and 1st places in the valence ordinal classification subtasks in English and Spanish, respectively.
We use gated recurrent units (GRU) along with convolutional neural network (CNN) inspired by REF .
Amobee at SemEval-2018 Task 1: GRU Neural Network with a CNN Attention Mechanism for Sentiment Classification
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