Improving Multi-label Emotion Classification via Sentiment Classification with Dual Attention Transfer Network

2018-10-01 · EMNLP 2018 10 · Jianfei Yu, Lu{\'\i}s Marujo, Jing Jiang, Pradeep Karuturi, William Brendel

In this paper, we target at improving the performance of multi-label emotion classification with the help of sentiment classification. Specifically, 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. Experimental results on two benchmark datasets demonstrate the effectiveness of our proposed method.

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Classification Emotion Classification General Classification Multi-Label ClassificationSentenceSentiment AnalysisSentiment ClassificationStock Market Prediction Transfer Learning

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