  In this paper, we present an experiment on using deep learning and transfer
learning techniques for emotion analysis in tweets and suggest a method to
interpret our deep learning models. The proposed approach for emotion analysis
combines a Long Short Term Memory (LSTM) network with a Convolutional Neural
Network (CNN). Then we extend this approach for emotion intensity prediction
using transfer learning technique. Furthermore, we propose a technique to
visualize the importance of each word in a tweet to get a better understanding
of the model. Experimentally, we show in our analysis that the proposed models
outperform the state-of-the-art in emotion classification while maintaining
competitive results in predicting emotion intensity.
