Preferential attachment

Graph generated using preferential attachment. A small number of nodes have a large number of incoming edges, whereas a large number of nodes have a small number of incoming edges.

A preferential attachment process is any of a class of processes in which some quantity, typically some form of wealth or credit, is distributed among a number of individuals or objects according to how much they already have, so that those who are already wealthy receive more than those who are not. "Preferential attachment" is only the most recent of many names that have been given to such processes. They are also referred to under the names Yule process, cumulative advantage, the rich get richer, and the Matthew effect. They are also related to Gibrat's law. The principal reason for scientific interest in preferential attachment is that it can, under suitable circumstances, generate power law distributions.[1] If preferential attachment is non-linear, measured distributions may deviate from a power law.[2] These mechanisms may generate distributions which are approximately power law over transient periods.[3][4]

  1. ^ Cite error: The named reference BAScience was invoked but never defined (see the help page).
  2. ^ Krapivsky, P. L.; Redner, S.; Leyvraz, F. (20 November 2000). "Connectivity of Growing Random Networks". Physical Review Letters. 85 (21): 4629–4632. arXiv:cond-mat/0005139. doi:10.1103/PhysRevLett.85.4629. PMID 11082613. S2CID 16251662.
  3. ^ Krapivsky, Paul; Krioukov, Dmitri (21 August 2008). "Scale-free networks as preasymptotic regimes of superlinear preferential attachment". Physical Review E. 78 (2): 026114. arXiv:0804.1366. doi:10.1103/PhysRevE.78.026114. PMID 18850904. S2CID 14292535.
  4. ^ Falkenberg, Max; Lee, Jong-Hyeok; Amano, Shun-ichi; Ogawa, Ken-ichiro; Yano, Kazuo; Miyake, Yoshihiro; Evans, Tim S.; Christensen, Kim (18 June 2020). "Identifying time dependence in network growth". Physical Review Research. 2 (2): 023352. arXiv:2001.09118. doi:10.1103/PhysRevResearch.2.023352.

From Wikipedia, the free encyclopedia · View on Wikipedia

Developed by Nelliwinne