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Modeling Innovation By A Kinetic Description Of The Patent Citation System, Gabor Csardi, Katherine J. Strandburg, Jan Tobochnik, Peter Erdi, Laszlo Zalanyi

Katherine J. Strandburg

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 …