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2020 , Vol. 64 >Issue 11: 77 - 86

DOI: https://doi.org/10.13266/j.issn.0252-3116.2020.11.009

Microblog Similarity Based on Super Network and Its Application in Microblog Public Opinion Topic Detection

  • Liang Xiaohe ,
  • Tian Ruya ,
  • Wu Lei ,
  • Zhang Xuefu
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  • Agricultural Information Institute of Chinese Academy of Agricultural Sciences, Beijing 100081

Received date: 2019-01-04

  Revised date: 2020-01-21

  Online published: 2020-06-05

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Abstract

[Purpose/significance] Accurate calculation of microblog similarity can improve the efficiency of microblog topic mining, and has practical significance for public opinion governance and information security. Aiming at the problem of sparse and high-dimensional microblog text, this paper proposes a super-edge similarity algorithm incorporating non-text features of microblog. [Method/process] The mechanism of microblog public opinion was analyzed, and the formation of microblog public opinion topic formation were expressed by super network model, and the algorithm of super-edge similarity was constructed by calculating the similarity of each subnet layer and the contribution of each subnet layer to the topic formation. [Result/conclusion] It was found that the similarity method proposed in this paper is helpful to improve the topic clustering effect of microblog public opinion information. Especially for micro blog with high similarity of literal expression, it has obvious subject differentiation.

Key words： super-edge similarity; topic detection; super network; microblog

Cite this article

Liang Xiaohe , Tian Ruya , Wu Lei , Zhang Xuefu . Microblog Similarity Based on Super Network and Its Application in Microblog Public Opinion Topic Detection[J]. Library and Information Service, 2020 , 64(11) : 77 -86 . DOI: 10.13266/j.issn.0252-3116.2020.11.009

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