Skip to main content
Modeling Innovation by a Kinetic Description of the Patent Citation System
Physica A (2007)
  • Gabor Csardi
  • Katherine J. Strandburg, DePaul University College of Law
  • Jan Tobochnik, Kalamazoo College
  • Peter Erdi
  • Laszlo Zalanyi

This paper reports results of a network theory approach to the study of the United States patent system. We model the patent citation network as a discrete time, discrete space stochastic dynamic system. From patent data we extract an attractiveness function, A(k, l), which determines the likelihood that a patent will be cited. A(k, l) shows power law aging and perferential attachment, the exponent of the latter is increasing since 1993, suggesting that patent citations are increasingly concentrated on a relatively small number of patents. In particular, our results appear consistent with an increasing patent “thicket”, in which more and more patents are issued on minor technical advances.

  • network,
  • patent
Publication Date
Citation Information
Gabor Csardi, Katherine J. Strandburg, Jan Tobochnik, Peter Erdi, and Laszlo Zalanyi. "Modeling Innovation by a Kinetic Description of the Patent Citation System" 374 PHYSICA A 783 (2007). Available at: