Measuring preferential attachment for evolving networks

Abstract

A key ingredient of current models proposed to capture the topological evolution of complex networks is the hypothesis that highly connected nodes increase their connectivity faster than their less connected peers, a phenomenon called preferential attachment. Measurements on four networks, namely the science citation network, Internet, actor collaboration and science coauthorship network indicate that the rate at which nodes acquire links depends on the node's degree, offering direct quantitative support for the presence of preferential attachment. We find that for the first two systems the attachment rate depends linearly on the node degree, while for the latter two the dependence follows a sublinear power law.

4 pages, 3 Figures, RevTex

References in corpus (5)

• Statistical mechanics of complex networks
• Evolution of the social network of scientific collaborations
• Clustering and preferential attachment in growing networks
• Dynamical and correlation properties of the Internet
• Preferencial growth: exact solution of the time dependent distributions

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