2004/08/28 by Gang Yan, Tao Zhou, Yan, Gang +5
Physics and Astronomy · #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Physical sciences #Statistical Mechanics (cond-mat.stat-mech) #cond-mat.dis-nn #cond-mat.stat-mech
paper · pdf · doi:10.48550/arxiv.cond-mat/0408631
9 eps figures, 4 pages
arxiv created 2004/08/28 · arxiv updated 2009/12/01
What is the underlying mechanism leading to power-law degree distributions of many natural and artificial networks is still at issue. We consider that scale-free networks emerges from self-organizing process, and such a evolving model is introduced in this letter. At each time step, a new node is added to the network and connect to some existing nodes randomly, instead of "preferential attachment" introduced by Barabási and Albert, and then the new node will connect with its neighbors' neighbors at a fixed probability, which is natural to collaboration networks and social networks of acquaintance or other relations between individuals. The simulation results show that those networks generated from our model are scale-free networks with satisfactorily large clustering coefficient.