Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
1999-07-05
Physics
Condensed Matter
Disordered Systems and Neural Networks
19 pages, 6 figures
Scientific paper
10.1016/S0378-4371(99)00291-5
Random networks with complex topology are common in Nature, describing systems as diverse as the world wide web or social and business networks. Recently, it has been demonstrated that most large networks for which topological information is available display scale-free features. Here we study the scaling properties of the recently introduced scale-free model, that can account for the observed power-law distribution of the connectivities. We develop a mean-field method to predict the growth dynamics of the individual vertices, and use this to calculate analytically the connectivity distribution and the scaling exponents. The mean-field method can be used to address the properties of two variants of the scale-free model, that do not display power-law scaling.
Albert Reka
Barabasi Albert-László
Jeong Hawoong
No associations
LandOfFree
Mean-field theory for scale-free random networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Mean-field theory for scale-free random networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Mean-field theory for scale-free random networks will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-30994