ScaleFree Network Growth by Ranking
Abstract
Network growth is currently explained through mechanisms that rely on node prestige measures, such as degree or fitness. In many real networks, those who create and connect nodes do not know the prestige values of existing nodes but only their ranking by prestige. We propose a criterion of network growth that explicitly relies on the ranking of the nodes according to any prestige measure, be it topological or not. The resulting network has a scalefree degree distribution when the probability to link a target node is any powerlaw function of its rank, even when one has only partial information of node ranks. Our criterion may explain the frequency and robustness of scalefree degree distributions in real networks, as illustrated by the special case of the Web graph.
 Publication:

Physical Review Letters
 Pub Date:
 June 2006
 DOI:
 10.1103/PhysRevLett.96.218701
 arXiv:
 arXiv:condmat/0602081
 Bibcode:
 2006PhRvL..96u8701F
 Keywords:

 89.75.Hc;
 89.20.Hh;
 Networks and genealogical trees;
 World Wide Web Internet;
 Condensed Matter  Disordered Systems and Neural Networks;
 Condensed Matter  Statistical Mechanics;
 Physics  Physics and Society
 EPrint:
 4 pages, 2 figures. We extended the model to account for ranking by arbitrarily distributed fitness. Final version to appear on Physical Review Letters