• DocumentCode
    2745479
  • Title

    Research on Cooperative Relations for Identifying Abnormal Vertices in Complex Financial Networks

  • Author

    Guo Yanli ; Xue Yaowen

  • Author_Institution
    Sch. of Econ. & Manage., Taiyuan Univ. of Sci. & Technol., Taiyuan, China
  • fYear
    2009
  • fDate
    6-7 June 2009
  • Firstpage
    37
  • Lastpage
    40
  • Abstract
    Theory and application of complex network is one of the hot spots in many discipline now. In our economic life financial network is one kind of complex social network. This paper constructs two types of conception models of complex finance network which weights has special meaning. Firstly, this paper uses UCINET (a social network analysis software) to find the clustering characteristic of the finance network. Secondly, this paper constructs a financial network which its weights mean capital transfers frequency and uses short-path algorithm to find the correlation ship of any two account vertexes. All these can provide the foundation for further studies.
  • Keywords
    complex networks; financial data processing; graph theory; social networking (online); UCINET; capital transfer frequency; clustering characteristic; complex economic life financial network; cooperative relation; correlation ship; identifying abnormal vertices; short-path algorithm; social network analysis software; Banking; Computer crime; Electronic commerce; Electronic mail; Finance; Financial management; Frequency; Intelligent networks; Social network services; Technology management; complex network; financial network; social network analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronic Commerce and Business Intelligence, 2009. ECBI 2009. International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-0-7695-3661-3
  • Type

    conf

  • DOI
    10.1109/ECBI.2009.70
  • Filename
    5189480