Scale-free networks with self-growing weight
Disordered Systems and Neural Networks
2007-07-24 v2 Physics and Society
Abstract
We present a novel type of weighted scale-free network model, in which the weight grows independently of the attachment of new nodes. The evolution of this network is thus determined not only by the preferential attachment of new nodes to existing nodes but also by self-growing weight of existing links based on a simple weight-driven rule. This model is analytically tractable, so that the various statistical properties, such as the distribution of weight, can be derived. Finally, we found that some type of social networks is well described by this model.
Keywords
Cite
@article{arxiv.cond-mat/0701314,
title = {Scale-free networks with self-growing weight},
author = {Takuma Tanaka and Toshio Aoyagi},
journal= {arXiv preprint arXiv:cond-mat/0701314},
year = {2007}
}
Comments
10 pages, 5 figures