  In this paper we describe a deep learning system that has been designed and
built for the WASSA 2017 Emotion Intensity Shared Task. We introduce a
representation learning approach based on inner attention on top of an RNN.
Results show that our model offers good capabilities and is able to
successfully identify emotion-bearing words to predict intensity without
leveraging on lexicons, obtaining the 13th place among 22 shared task
competitors.
