Estimating the dynamics of kernel-based evolving networks

  • Gábor Csárdi
  • Katherine Strandburg
  • László Zalányi
  • Jan Tobochnik
  • Péter érdi

Abstract

In this paper we present the application of a novel methodology to scientific citation and collaboration networks. This methodology is designed for understanding the governing dynamics of evolving networks and relies on an attachment kernel, a scalar function of node properties, that stochastically drives the addition and deletion of vertices and edges. We illustrate how the kernel function of a given network can be extracted from the history of the network and discuss other possible applications.

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Copyright information

© Springer 2010

Authors and Affiliations

  • Gábor Csárdi
    • 1
    • 2
  • Katherine Strandburg
    • 3
  • László Zalányi
    • 2
  • Jan Tobochnik
    • 4
  • Péter érdi
    • 1
  1. 1.Center for Complex Systems StudiesKalamazooUSA
  2. 2.Department of BiophysicsKFKI Research Institute for Particle and Nuclear Physics of the Hungarian Academy of SciencesBudapestHungary
  3. 3.DePaul University — College of LawChicagoUSA
  4. 4.Department of Physics and Center for Complex Systems StudiesKalamazoo CollegeKalamazooUSA

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