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In this paper we describe a deep learning system that has been designed andbuilt for the WASSA 2017 Emotion Intensity Shared Task. We introduce arepresentation learning approach based on inner attention on top of an RNN.Results show that our model offers good capabilities and is able tosuccessfully identify emotion-bearing words to predict intensity withoutleveraging on lexicons, obtaining the 13th place among 22 shared taskcompetitors.

EmoAtt at EmoInt-2017: Inner attention sentence embedding for Emotion Intensity