Emergence of Scaling in Random Networks
Abstract
Systems as diverse as genetic networks or the World Wide Web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scalefree powerlaw distribution. This feature was found to be a consequence of two generic mechanisms: (i) networks expand continuously by the addition of new vertices, and (ii) new vertices attach preferentially to sites that are already well connected. A model based on these two ingredients reproduces the observed stationary scalefree distributions, which indicates that the development of large networks is governed by robust selforganizing phenomena that go beyond the particulars of the individual systems.
 Publication:

Science
 Pub Date:
 October 1999
 DOI:
 10.1126/science.286.5439.509
 arXiv:
 arXiv:condmat/9910332
 Bibcode:
 1999Sci...286..509B
 Keywords:

 Condensed Matter  Disordered Systems and Neural Networks;
 Condensed Matter  Statistical Mechanics;
 Nonlinear Sciences  Adaptation and SelfOrganizing Systems
 EPrint:
 11 pages, 2 figures