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International Conference on Complex Systems (ICCS2006)

Complex knowledge networks and invention collaborations

Thomas Brantle
Stevens Institute of Technology

M. Hosein Fallah
Stevens Institute of Technology

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     Last modified: August 13, 2006

Abstract
Underlying the process of innovation is a complex network of interactions and collaborations among scientists and engineers across many organizations and technology domains. We study knowledge and innovation flows as characterized by the network of invention collaborations, investigate its scale free power law properties and discuss the importance of these networks and their underlying processes to the advancement of knowledge exchange and technological innovation. We illustrate that this area of research while traditionally investigated via econometric modeling and statistical data analysis may be further examined and explained via a complex network analysis approach using the tools and techniques of statistical mechanics and complex network analysis. In particular, we demonstrate that the network node degree probability distribution may be characterized by a power law. For that reason the probability that a node or inventor collaborator is highly connected is statistically more likely than would be expected via random connections and associations. The network’s properties are consequently determined by a relatively small number of highly connected inventors and collaborators known as hubs. We also highlight several potential application areas for further investigation via a complex network analysis approach.
Keywords: Complex Networks, Innovation, Knowledge Flows, Patents, Inventors, Collaboration, Power Laws, Probability Distributions, Scale Free Networks




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