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Full-Text Articles in Physics
Patent Citation Networks Revisited: Signs Of A Twenty-First Century Change, Katherine J. Strandburg, Gabor Csardi, Laszlo Zalanyi, Jan Tobochnik, Peter Erdi
Patent Citation Networks Revisited: Signs Of A Twenty-First Century Change, Katherine J. Strandburg, Gabor Csardi, Laszlo Zalanyi, Jan Tobochnik, Peter Erdi
Katherine J. Strandburg
This Article reports an empirical study of the network composed of patent “nodes” and citation “links” between them. It builds on an earlier study, in which we argued that trends in the growth of the patent citation network provide evidence that the explosive growth in patenting in the late twentieth century was due at least in part to the issuance of increasingly trivial patents. We defined a measure of patent stratification based on comparative probability of citation; an increase in this measure suggests that the USPTO is issuing patents of comparatively less technological significance. Provocatively, we found that stratification increased …
Modeling Innovation By A Kinetic Description Of The Patent Citation System, Gabor Csardi, Katherine J. Strandburg, Jan Tobochnik, Peter Erdi, Laszlo Zalanyi
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 …
Estimating The Dynamics Of Kernel-Based Evolving Networks, Gabor Csardi, Katherine J. Strandburg, Laszlo Zalanyi, Jan Tobochnik, Peter Erdi
Estimating The Dynamics Of Kernel-Based Evolving Networks, Gabor Csardi, Katherine J. Strandburg, Laszlo Zalanyi, Jan Tobochnik, Peter Erdi
Katherine J. Strandburg
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, which 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.