Stationary States of a Random Copying Mechanism over a Complex Networks
  An analytical approach to network dynamics is used to show that when agents copy their state randomly the network arrives to a stationary status in which the distribution of states is independent of the agents degree. The effects of network topology on the process are characterized introducing a quantity called influence and studying its behavior for scale-free and random networks. We show that for this model degree averaged means are constant in time regardless of the number of states involved. 
Cesar A. Hidalgo, Francisco Claro, Pablo A. Marquet