Stationary state structure of a random copying mechanism over a complex network
Abstract
An analytical approach to network dynamics is used to show that when agents copy their state randomly, the network arrives to a stationary regime in which the distribution of states is independent of the degree. The effects of network topology on the process are characterized introducing a quantity called influence and studying its behavior for scalefree and random networks. We show that for this model degree averaged quantities are constant in time regardless of the number of states involved.
 Publication:

Physica A Statistical Mechanics and its Applications
 Pub Date:
 August 2005
 DOI:
 10.1016/j.physa.2005.01.035
 arXiv:
 arXiv:condmat/0411295
 Bibcode:
 2005PhyA..353..674H
 Keywords:

 Disordered Systems and Neural Networks
 EPrint:
 11 pages, 3 Figures, article class