  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-recurrent-units (GRU) with a convolution neural network (CNN) attention
mechanism and training stacking-based ensembles for each of the sub-tasks. Our
algorithm reached 3rd and 1st places in the valence ordinal classification
sub-tasks in English and Spanish, respectively.
