Discovering Strong Communities with User Engagement and Tie Strength

  • Fan Zhang
  • Long Yuan
  • Ying Zhang
  • Lu Qin
  • Xuemin Lin
  • Alexander Zhou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10827)


In this paper, we propose and study a novel cohesive subgraph model, named (\(k\),\(s\))-core, which requires each user to have at least k familiars or friends (not just acquaintances) in the subgraph. The model considers both user engagement and tie strength to discover strong communities. We compare the (\(k\),\(s\))-core model with \(k\)-core and \(k\)-truss theoretically and experimentally. We propose efficient algorithms to compute the (\(k\),\(s\))-core and decompose the graph by a particular sub-model \(k\)-fami. Extensive experiments show (1) our (\(k\),\(s\))-core and \(k\)-fami are effective cohesive subgraph models and (2) the (\(k\),\(s\))-core computation and \(k\)-fami decomposition are efficient on various real-life social networks.



Fan Zhang and Long Yuan are supported by Huawei YBN2017100007. Ying Zhang is supported by ARC FT170100128 and DP180103096. Lu Qin is supported by ARC DP160101513. Xuemin Lin is supported by NSFC 61672235, ARC DP170101628, DP180103096 and Huawei YBN2017100007.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Fan Zhang
    • 1
  • Long Yuan
    • 1
  • Ying Zhang
    • 2
  • Lu Qin
    • 2
  • Xuemin Lin
    • 1
  • Alexander Zhou
    • 3
  1. 1.University of New South WalesSydneyAustralia
  2. 2.Centre for AIUniversity of Technology SydneySydneyAustralia
  3. 3.University of QueenslandBrisbaneAustralia

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