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Semi-supervised Sentiment Classification Method Based on Weibo Social Relationship

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Web Information Systems and Applications (WISA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11817))

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Abstract

Sentiment classification of microblog text is one of the hotspots and important research issues in text sentiment analysis. Aiming at the problem that the existing researches mostly assume that the micro-blog sentiments are independent of each other and have strong dependence on the training set, a semi-supervised sentiment classification method based on Weibo social relationship is proposed. The method utilizes the user’s theme sentimental consistency and the approval of social relationships (like and repost) in Weibo to establish the sentimental relationship between microblogs to solve the problem that microblog sentiments are independent of each other. Semi-supervised sentimental classification model is constructed by establishing the sentimental relationship between labeled micro-blog and unlabeled micro-blog, which reduced the dependence on training set. Specifically, the semi-supervised sentiment classification method was constructed by constructing a microblog sentimental relationship matrix using the Laplacian matrix of the above microblog social relationship graph, and adding to the text content based classification model. Climbing the real dataset of Sina Weibo for experiment, the experimental results showed that the method is superior to other typical sentiment classification methods in terms of accuracy and recall rate. The validity of this method is verified and the dependence on training data set is reduced to a certain extent.

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Acknowledgments

This work was supported by the National Key Research and Development Plan (2016YFC0101500) and the Fundamental Research Funds for the Central Universities (N161602002), the Natural Science Foundation of China under grant (No. 61532007, 61370076), the Natural Science Foundation of Jiangsu Province under grant No. 15KJB520001. This work was partly supported by the Natural Science Foundation of Jiangsu Province of China under grant NO. BK2012209, Science and Technology Program of Suzhou in China under grant NO. SYG201409. Finally, the authors would like to thank the anonymous reviewers for their constructive advices.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Changshu Institute of Technology, Suhzou, China

    Wei Liu & Mingxin Zhang

Authors
  1. Wei Liu
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  2. Mingxin Zhang
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Correspondence to Mingxin Zhang .

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Editors and Affiliations

  1. Southeast University, Nanjing, China

    Weiwei Ni

  2. Tianjin University, Tianjin, China

    Xin Wang

  3. Wuhan University, Wuhan, China

    Wei Song

  4. Tianjin University of Technology, Tianjin, China

    Yukun Li

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Liu, W., Zhang, M. (2019). Semi-supervised Sentiment Classification Method Based on Weibo Social Relationship. In: Ni, W., Wang, X., Song, W., Li, Y. (eds) Web Information Systems and Applications. WISA 2019. Lecture Notes in Computer Science(), vol 11817. Springer, Cham. https://doi.org/10.1007/978-3-030-30952-7_47

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  • DOI: https://doi.org/10.1007/978-3-030-30952-7_47

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-30951-0

  • Online ISBN: 978-3-030-30952-7

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