On Link Stability Detection for Online Social Networks

  • Ji ZhangEmail author
  • Xiaohui Tao
  • Leonard Tan
  • Jerry Chun-Wei LinEmail author
  • Hongzhou Li
  • Liang Chang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11029)


Link stability detection has been an important and long-standing problem within the link prediction domain. However, it has often been overlooked as being trivial and has not been adequately dealt with in link prediction. In this paper, we present an innovative method: Multi-Variate Vector Autoregression (MVVA) analysis to determine link stability. Our method adopts link dynamics to establish stability confidence scores within a clique sized model structure observed over a period of 30 days. Our method also improves detection accuracy and representation of stable links through a user-friendly interactive interface. In addition, a good accuracy to performance trade-off in our method is achieved through the use of Random Walk Monte Carlo estimates. Experiments with Facebook datasets reveal that our method performs better than traditional univariate methods for stability identification in online social networks.


Link stability Graph theory Online social networks Hamiltonian Monte Carlo (HMC) 



This research was partially supported by Guangxi Key Laboratory of Trusted Software (No. kx201615), Shenzhen Technical Project (JCYJ20170307151733005 and KQJSCX20170726103424709), Capacity Building Project for Young University Staff in Guangxi Province, Department of Education of Guangxi Province (No. ky2016YB149).


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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Faculty of Engineering and SciencesThe University of Southern QueenslandToowoombaAustralia
  2. 2.Harbin Institute of Technology Shenzhen Graduate SchoolShenzhenChina
  3. 3.School of Life and Environmental ScienceGuilin University of Electronic TechnologyGuilinChina
  4. 4.Guangxi Key Laboratory of Trusted SoftwareGuilin University of Electronic TechnologyGuilinChina

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