Abstract
Social and economic networks are becoming increasingly popular in the last ten years, because of both the application of game theory to the network formation processes4, and the study of stochastic processes that fit the statistical properties of real world social networks.5 In the very recent years there have also been attempts to combine the contribution of these two streams of research, trying to find strategic models whose equilibria resemble the empirical data.6 A well known source of debate in the game theoretical approach is the incompatibility between stability and efficiency: in most of the models Nash equilibria are actually not the network architectures that maximize the overall sum of utilities, as surveyed in Jackson (2003). On the other hand the econophysics approach is not interested in the utility of single nodes but has other measures of efficiency, which are essentially the probabilities of the network to maintain certain properties after random deletion of links or nodes.
The seminal paper is by Jackson and Wolinsky (1996), see Jackson (2006) for a survey of this literature.
The starting point of this second stream of research can be considered Albert and Barabási (1999), see Newman (2003) for a survey. Let us refer to this second scientific contribution as the econophysics approach.
As an example see Jackson and Rogers (2007).
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Giansante, S., Kirman, A., Markose, S., Pin, P. (2007). The Grass is Always Greener on the Other Side of the Fence: The Effect of Misperceived Signalling in a Network Formation Process. In: Consiglio, A. (eds) Artificial Markets Modeling. Lecture Notes in Economics and Mathematical Systems, vol 599. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73135-1_16
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