Detecting overlapping communities via expanding core regions

Qingyao Liu, Dingda Yang, Zhongzheng Zhang, Jianwu Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A social circle usually has some cores. Inspired by this phenomenon, we consider that a community in a complex network is also formed around one or several core vertices, called core region. We define the core score of a vertex to reflect its ability to attract other vertices. Utilizing the core scores of vertices, we address how to find the core region of one community, and then we apply local expansion and optimization to detect communities based on these core regions. Besides detecting community structure, our method can detect some abnormal vertices that are the hubs of network. Experimental results based on artificial networks and real-world networks show that our method is more effective than some usual methods.

Original languageEnglish
Title of host publicationProceedings - 2020 International Conference on Computing and Data Science, CDS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages231-237
Number of pages7
ISBN (Electronic)9781728171067
DOIs
Publication statusPublished - Aug 2020
Event2020 International Conference on Computing and Data Science, CDS 2020 - Stanford, United States
Duration: 1 Aug 20202 Aug 2020

Publication series

NameProceedings - 2020 International Conference on Computing and Data Science, CDS 2020

Conference

Conference2020 International Conference on Computing and Data Science, CDS 2020
Country/TerritoryUnited States
CityStanford
Period1/08/202/08/20

Keywords

  • Community detection
  • Core region
  • Hub
  • Local expansion

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