Identification Method of Microblog Opinion Targets Involved in Cases Based on Dual Topic Representation
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TP18

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    Abstract:

    The identification of opinion targets in microblog is the basis of analyzing network public opinion involved in cases. At present, the identification method of opinion targets based on topic representation needs to preset a fixed number of topics, and the final results rely on artificial inference. In order to solve these problems, this study proposes a weak supervision method, which only uses a small number of labelled comments to automatically identify the opinion targets in microblog. The specific implementation is as follows. Firstly, the comments are encoded and reconstructed twice based on the variational dual topic representation network to obtain rich topic features. Secondly, a small number of labelled comments are used to guide the topic representation network to automatically identify the opinion targets. Finally, the reconstruction loss of double topic representation and the classification loss of opinion targets identification are optimized together by the joint training strategy, to classify comments of opinion targets automatically and mine target terms. Experiments are carried out on two data sets of microblogs involved in cases. The results show that the proposed model outperforms several baseline models in the classification of opinion targets, topic coherence, and diversity of target terms.

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相艳,余正涛,郭军军,黄于欣,线岩团.利用双主题表征的涉案微博评价对象识别方法.软件学报,2023,34(4):1811-1823

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History
  • Received:August 16,2020
  • Revised:February 04,2021
  • Adopted:
  • Online: July 07,2022
  • Published:
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