EmoAtt at EmoInt-2017: Inner attention sentence embedding for Emotion Intensity
Edison Marrese-Taylor, Yutaka Matsuo · 2017
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 emotionbearing words to predict intensity without leveraging on lexicons, obtaining the 13 th place among 22 shared task competitors.