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Abstract

Random walk on a real social networking service consisting of 2271 nodes is analyzed on the basis of the statistical-thermodynamics formalism to find phase transitions in network structure. Each phase can be related to a characteristic local structure of the network such as a cluster or a hub. For this purpose, the generalized transition matrix is introduced, whose largest eigenvalue yields statistical structure functions. The weighted visiting frequency related to the Gibbs probability measure, which is useful for extracting characteristic local structures, is obtained from the products of the right and left eigenvectors corresponding to the largest eigenvalue. An algorithm to extract the characteristic local structure of each phase is also suggested on the basis of this weighted visiting frequency.

Journal

  • Progress of theoretical physics

    Progress of theoretical physics 124(1), 27-52, 2010-07-25

    Publication Office, Progress of Theoretical Physics

References:  16

Cited by:  2

Codes

  • NII Article ID (NAID)
    110007703065
  • NII NACSIS-CAT ID (NCID)
    AA00791455
  • Text Lang
    ENG
  • Article Type
    Journal Article
  • ISSN
    0033068X
  • NDL Article ID
    10764111
  • NDL Source Classification
    ZM35(科学技術--物理学)
  • NDL Call No.
    Z53-A468
  • Data Source
    CJP  CJPref  NDL  NII-ELS 
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