Efficient Incremental Laplace Centrality Algorithm for Dynamic Networks

  • Rui Portocarrero SarmentoEmail author
  • Mário Cordeiro
  • Pavel Brazdil
  • João Gama
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 689)


Social Network Analysis (SNA) is an important research area. It originated in sociology but has spread to other areas of research, including anthropology, biology, information science, organizational studies, political science, and computer science. This has stimulated research on how to support SNA with the development of new algorithms. One of the critical areas involves calculation of different centrality measures. The challenge is how to do this fast, as many increasingly larger datasets are available. Our contribution is an incremental version of the Laplacian Centrality measure that can be applied not only to large graphs but also to dynamically changing networks. We have conducted several tests with different types of evolving networks. We show that our incremental version can process a given large network, faster than the corresponding batch version in both incremental and full dynamic network setups.



This work is financed by the ERDF – European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme within project \(\ll \)POCI-01-0145-FEDER-006961\(\gg \) , and by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) as part of project UID/EEA/50014/2013. Rui Portocarrero Sarmento also gratefully acknowledges funding from FCT (Portuguese Foundation for Science and Technology) through a PhD grant (SFRH/BD/119108/2016)


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Rui Portocarrero Sarmento
    • 1
    Email author
  • Mário Cordeiro
    • 1
  • Pavel Brazdil
    • 2
  • João Gama
    • 2
  1. 1.PRODEI - FEUPUniversity of PortoPortoPortugal
  2. 2.INESC TEC - LIAADPortoPortugal

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