In this paper, we target at improving the performance of multi-label emotion classification with the help of sentiment classification.
we propose a new transfer learning architecture to divide the sentence representation into two different feature spaces, which are expected to respectively capture the general sentiment words and the other important emotion-specific words via a dual attention mechanism.