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2020 , Vol. 64 >Issue 9: 142 - 152

DOI: https://doi.org/10.13266/j.issn.0252-3116.2020.09.016

Research Progress in Community Detection of Online Social Networks

  • Zhang Haitao ,
  • Zhou Honglei ,
  • Zhang Xinrui ,
  • Sun Tong
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  • 1 Management School of Jilin University, Changchun 130022;
    2 The Information Resource Research Center of Jilin University, Changchun 130022

Received date: 2019-11-12

  Revised date: 2020-02-07

  Online published: 2020-05-05

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Abstract

[Purpose/significance] Taking online social network as the research object, and through the literature combing to accurately capture the development trend and research hotspots of community discovery, and exploring how to mine hidden communities in large-scale social networks, which has theoretical and practical significance. [Method/process] Using CNKI database, Web of Science core collection and related international conference documents as data sources. The CiteSpace visual analysis tool was used to quantitatively study hotspot keywords, topic evolution paths and co-cited documents. And the topic research content was reviewed from 3 dimensions:community discovery method, algorithm implementation and application practice. [Result/conclusion] There is still much room for development in the current research field. In the future, we should pay attention to optimization and innovation of algorithms, differentiation and expansion of application scenarios, and cross-disciplinary research on interdisciplinary knowledge and cutting-edge technology methods.

Key words： online social network; community detection; dynamic community evolution; research progress

Cite this article

Zhang Haitao , Zhou Honglei , Zhang Xinrui , Sun Tong . Research Progress in Community Detection of Online Social Networks[J]. Library and Information Service, 2020 , 64(9) : 142 -152 . DOI: 10.13266/j.issn.0252-3116.2020.09.016

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