Abstract
In recent times the possibility of using the tools of statistical physics to analyze the rich dynamical behaviors observed in social, technological, and economical systems has attracted a lot of attention from the physics community (Arthur et al. 1997, Mantegna and Stanley 1999, Bouchaud and Potters 2000). So far, one of the main contributions to these fields has been the analysis of simple models that capture the basic features of the investigated phenomena. The goal is to identify the relevant parameters as well as the essential mechanisms governing their dynamics with the hope that this information will help us to understand the physical behavior of real complex systems. A real part of this effort has been devoted to the characterization of real networks, identifying their main features, and understanding how they arise (Watts and Strogatz 1998, Barabasi and Albert 1999, Strogatz 2001, Dorogovtsev and Mendes 2002, Albert and Barabasi 2002).
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Diaz-Guilera, A., Lozano, S., Arenas, A. (2009). Propagation of Innovations in Complex Patterns of Interaction. In: Pyka, A., Scharnhorst, A. (eds) Innovation Networks. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92267-4_9
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DOI: https://doi.org/10.1007/978-3-540-92267-4_9
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