• DocumentCode
    245847
  • Title

    Self-Stabilizing Selection of Influential Users in Social Networks

  • Author

    Yihua Ding ; Wang, James Z. ; Srimani, Pradip K.

  • Author_Institution
    Sch. of Comput., Clemson Univ., Clemson, SC, USA
  • fYear
    2014
  • fDate
    19-21 Dec. 2014
  • Firstpage
    1558
  • Lastpage
    1565
  • Abstract
    Selection of Influential Users is an essential task in influence propagation schemes in social networks. Considering the phenomenon of asymmetric influences between neigh boring users and different sensitivities of users to influences, we propose to select the users in the minimal weighted positive influence dominating set of a social network graph as the influential users to maximize the speed of the propagation. We present the first polynomial time self-stabilizing algorithm for minimal weighted positive influence dominating set in an arbitrary social network. Starting from an arbitrary initial state, the algorithm terminates in O(n3) steps using a distributed scheduler, where n is the number of nodes in the graph. Space requirement at each node is O(log n) bits. Experiments are conducted to verify the correctness and efficiency of the proposed algorithm.
  • Keywords
    computational complexity; fault tolerant computing; graph theory; social networking (online); user interfaces; graph; influence propagation schemes; influential users; polynomial time; self-stabilizing selection; social networks; Algorithm design and analysis; Computational modeling; Network topology; Protocols; Sensitivity; Social network services; Time complexity; Distributed Scheduler; Influential Users; Minimal Weighted Positive Influence Dominating Set; Self-Stabilizing Algorithms; Social Networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on
  • Conference_Location
    Chengdu
  • Print_ISBN
    978-1-4799-7980-6
  • Type

    conf

  • DOI
    10.1109/CSE.2014.288
  • Filename
    7023799