JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2018, Vol. 53 ›› Issue (9): 35-39.doi: 10.6040/j.issn.1671-9352.1.2017.003

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Reader emotion classification with news and comments

  

  1. Natural Language Processing Laboratory, Soochow University, Suzhou 215006, Jiangsu, China
  • Received:2017-07-04 Online:2018-09-20 Published:2018-09-10

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Abstract: The news and comments are important resources to classify the reader emotion. However, previous studies only used news texts or mixed two types of texts as a general feature, which did not make the best use of the differences and connections between different textual features. Based on it, the paper proposed a new approach named dual-channel LSTM, which treated two types of texts as different features. First, the approach learned a LSTM representation with a LSTM recurrent neural network. Then, it proposed a joint learning method to learn the relationship between the features. Empirical studies demonstrate the effectiveness of the proposed approach to reader emotion classification.

Key words: reader emotion classification, joint learning, dual-channel LSTM

CLC Number: 

  • TP391
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