Social Percolators and Self Organized Criticality

  • Gérard Weisbuch
  • Sorin Solomon
  • Dietrich Stauffer
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 503)


We discuss the influence of information contagion on the dynamics of choices in social networks of heterogeneous buyers. In the case of non-adaptive agents, the dynamics results in either the contagion process being stuck and very few agents actually buying (flops) or in a ‘hit’ where most agents a priori interested in getting the product actually buy it. We also show that when buyers and sellers try to adjust bids and asks the tatonement process does not converge to equilibrium at some intermediate market share and that large amplitude swings are actually observed across the percolation threshold.


Percolation Threshold Refractory Period Contagion Process Percolation Transition Movie Industry 
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  1. Ahmed E. and H.A. Abdusalam, (2000), Eur. Phys. J. B, 16, 569.CrossRefGoogle Scholar
  2. Bak, P. and Tang, C. Earthquakes as an SOC phenomenon, J. Geophys. Res. 94, 15635–15637 (1989).CrossRefGoogle Scholar
  3. Broadbent, S.K. and J.M. Hammersley, Percolation processes I. Crystals and mazes, Proc. Camb. Phil. Soc., 53, 629–641, (1957).CrossRefGoogle Scholar
  4. Farrell W. (1998), “How hits happen”, HarperCollins, New York. Goldenberg J., B. Libai, S. Solomon, N. Jan, D. Stauffer, 2000, Marketing percolation Physica A, 284, 335–347.Google Scholar
  5. Huang, Z.F. (2000)Int. J. Mod. Phys.C 11, 287, and Eur.J. Phys. B16, 379.Google Scholar
  6. Kar Gupta, A. and Stauffer, D. (2000), Int. J. Mod. Phys. C 11, 695.Google Scholar
  7. Levy H., Levy M., and Solomon S., (2000)Microscopic Simulation of Financial MarketsAcademic Press, New York.Google Scholar
  8. Lux T. and Ausloos M., (2001), “Market Fluctuations I: Scaling, Multi-Scaling and Their Possible Origins” in A. Bunde and H.-J. Schellnhuber (Hg.):Facets of Universality in Complex Systems: Climate Biodynamics and Stock MarketsBerlin.Google Scholar
  9. Plouraboué F., Steyer A. and Zimmermann J.B.Economics of Innovation and New Technology6, 73, (1998).CrossRefGoogle Scholar
  10. Solomon S., Weisbuch G., de Arcangelis L., Jan N., and Stauffer D. (2000) Physica A 277, 239.Google Scholar
  11. Stauffer D. and Aharony A., (1994) “Introduction to Percolation Theory”, Taylor and Francis, London.Google Scholar
  12. Steyer A. and Zimmermann J.B., “Self Organised Criticality in Economic and Social Networks: The case of innovation diffusion” proceedings of the Workshop on Economics and Heterogeneous Interacting (2000).Google Scholar
  13. Watts D. J. and S. H. Strogatz, Nature, 393, 440, (1998).CrossRefGoogle Scholar
  14. G. Weisbuch and D. Stauffer “Hits and Flops Dynamics” Physica A, 287, 3–4, 563–576, (2000).Google Scholar
  15. G. Weisbuch and S. Solomon “Self Organized Percolation and Critical Sales Fluctuations” Int. Jour. Mod. Phys. C, Vol 11, No. 6,1263–1272, (2000).CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Gérard Weisbuch
    • 1
  • Sorin Solomon
    • 2
  • Dietrich Stauffer
    • 3
  1. 1.Laboratoire de Physique Statistique de l’Ecole Normale SupérieureParis Cedex 5France
  2. 2.Theoretical Physics DepartmentRacah Institute of Physics Hebrew University of JerusalemJerusalemIsrael
  3. 3.Institute for Theoretical PhysicsCologne UniversityKölnGermany

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