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.
There was a gated recurrent units (GRU) based model proposed by REF with a convolution neural network (CNN) attention mechanism and training stacking-based ensembles.
Amobee at SemEval-2018 Task 1: GRU Neural Network with a CNN Attention Mechanism for Sentiment Classification
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