Self-organization of knowledge economies

F. Lafond

Journal of Economic Dynamics and Control 52, 150 (2015)

#socialnetworks#innovation#economics

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LQ placeholderSimulations for 106 periods, using different social networks.

Simulations for 106 periods, using different social networks.

Suppose that homogenous agents fully consume their time to invent new ideas and learn ideas from their friends. If the social network is complete and agents pick friends and ideas of friends uniformly at random, the distribution of ideas’ popularity is an extension of the Yule–Simon distribution. It has a power-law tail, with an upward or downward curvature. For infinite population it converges to the Yule–Simon distribution. The power law is steeper when innovation is high. Diffusion follows logistic curves.

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Degree-correlations in a bursting dynamic network model

F. Vanni, P. Barucca

Journal of Economic Interaction and Coordination

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Scale of non-locality for a system of n particles

S. Talaganis, I. Teimouri

Sub. to Physical Review D

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Changes to Gate Closure and its impact on wholesale electricity prices: The case of the UK

A. Facchini, A. Rubino, G. Caldarelli, G. Liddo

Energy Policy

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How much can we influence the rate of innovation?

T. Fink, M. Reeves

Science Advances

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The statistical physics of real-world networks

G. Cimini, T. Squartini, F. Saracco, D. Garlaschelli, A. Gabrielli, G. Caldarelli

Nature Reviews Physics

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PopRank: Ranking pages’ impact and users’ engagement on Facebook

A. Zaccaria, M. Vicario, W. Quattrociocchi, A. Scala, L. Pietronero

PLoS ONE

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