Scaling and Percolation in the Small-World Network Model

M. E. J. Newman and D. J. Watts

Working Papers from Santa Fe Institute

Abstract: In this paper we study the small-world network model of Watts and Strogatz, which mimics some aspects of the structure of networks of social interactions. We argue that there is one non-trivial length-scale in the model, analogous to the correlation length in other systems, which is well-defined in the limit of infinite system size and which diverges continuously as the randomness in the network tends to zero, giving a normal critical point in this limit. This length-scale governs the cross-over from large- to small-world behavior in the model, as well as the number of vertices in a neighborhood of given radius on the network. We derive the value of the single critical exponent controlling behavior in the critical region and the finite size scaling form for the average vertex-vertex distance on the network, and, using series expansion and Pade approximants, find an approximate analytic form for the scaling function. We calculate the effective dimension of small-world graphs and show that this dimension varies as a function of the length-scale on which it is measured, in a manner reminiscent of multifractals. We also study the problem of site percolation on small-world networks as a simple model of disease propagation, and derive an approximate expression for the percolation probability at which a giant component of connected vertices first forms (in epidemiological terms, the point at which an epidemic occurs). The typical cluster radius satisfies the expected finite size scaling form with a cluster size exponent close to that for a random graph. All our analytic results are confirmed by extensive numerical simulations of the model.

Appears in Phys. Rev. E 60, 7332-7342 (1999).

Keywords: Small world; social interaction; networks; graph theory; phase transitions; percolation (search for similar items in EconPapers)
Date: 1999-05
New Economics Papers: this item is included in nep-evo
References: Add references at CitEc
Citations: View citations in EconPapers (71)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wop:safiwp:99-05-034

Access Statistics for this paper

More papers in Working Papers from Santa Fe Institute Contact information at EDIRC.
Bibliographic data for series maintained by Thomas Krichel ().