A simple model of global cascades on random networks.

Duncan J Watts
Author Information
  1. Duncan J Watts: Department of Sociology, Columbia University New York, NY 10027.

Abstract

The origin of large but rare cascades that are triggered by small initial shocks is a phenomenon that manifests itself as diversely as cultural fads, collective action, the diffusion of norms and innovations, and cascading failures in infrastructure and organizational networks. This paper presents a possible explanation of this phenomenon in terms of a sparse, random network of interacting agents whose decisions are determined by the actions of their neighbors according to a simple threshold rule. Two regimes are identified in which the network is susceptible to very large cascades-herein called global cascades-that occur very rarely. When cascade propagation is limited by the connectivity of the network, a power law distribution of cascade sizes is observed, analogous to the cluster size distribution in standard percolation theory and avalanches in self-organized criticality. But when the network is highly connected, cascade propagation is limited instead by the local stability of the nodes themselves, and the size distribution of cascades is bimodal, implying a more extreme kind of instability that is correspondingly harder to anticipate. In the first regime, where the distribution of network neighbors is highly skewed, it is found that the most connected nodes are far more likely than average nodes to trigger cascades, but not in the second regime. Finally, it is shown that heterogeneity plays an ambiguous role in determining a system's stability: increasingly heterogeneous thresholds make the system more vulnerable to global cascades; but an increasingly heterogeneous degree distribution makes it less vulnerable.

References

  1. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics. 1999 Aug;60(2 Pt A):1412-27 [PMID: 11969901]
  2. Phys Rev Lett. 1993 May 24;70(21):3347-3350 [PMID: 10053845]
  3. Proc Biol Sci. 1999 Apr 22;266(1421):859-67 [PMID: 10343409]
  4. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics. 2000 May;61(5A):4877-82 [PMID: 11031529]
  5. Phys Rev Lett. 2000 Dec 18;85(25):5468-71 [PMID: 11136023]
  6. Nature. 2001 Mar 8;410(6825):268-76 [PMID: 11258382]
  7. Nature. 2000 Jul 27;406(6794):378-82 [PMID: 10935628]
  8. Phys Rev E Stat Nonlin Soft Matter Phys. 2001 Aug;64(2 Pt 2):026118 [PMID: 11497662]
  9. Science. 1987 May 29;236(4805):1092-4 [PMID: 17799664]
  10. Phys Rev Lett. 1987 Jul 27;59(4):381-384 [PMID: 10035754]
  11. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics. 1999 Dec;60(6 Pt B):7332-42 [PMID: 11970678]

Word Cloud

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