• DocumentCode
    169242
  • Title

    Covert nodes mining in social networks based on games theory

  • Author

    Atiao Yang ; Yong Tang ; Jiangbin Wang ; Jieming Chen

  • Author_Institution
    Dept. of Comput. Sci., South China Normal Univ., Guangzhou, China
  • fYear
    2014
  • fDate
    21-23 May 2014
  • Firstpage
    541
  • Lastpage
    545
  • Abstract
    The problem of discovering covert nodes in social network has been widely studied because of its tremendous number of applications in determining critical points in social network, such as detecting terrorist, recommending item for possible customer, finding the source of spreading gossip, etc. In this paper, we utilize game theory to solve this problem. Firstly, we propose the model which analyzes game in the influence transmission. Then we obtain each nodes contribution by calculating the nodes earning in game. The feasibility and effectiveness of our method were verified on a simulation dataset and a real dataset.
  • Keywords
    data mining; game theory; social networking (online); covert nodes mining; critical points; games theory; influence transmission; real dataset; simulation dataset; social network; Collaboration; Game theory; Games; Network topology; Peer-to-peer computing; Social network services; Topology; Covert node problem; Dynamic games; Social network; repeated games;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Supported Cooperative Work in Design (CSCWD), Proceedings of the 2014 IEEE 18th International Conference on
  • Conference_Location
    Hsinchu
  • Type

    conf

  • DOI
    10.1109/CSCWD.2014.6846902
  • Filename
    6846902