Mechanism for linear preferential attachment in growing networks

Xinping Xu, Feng Liu and Lianshou Liu

Physica A: Statistical Mechanics and its Applications, 2005, vol. 356, issue 2, 662-670

Abstract: The network properties of a graph ensemble subject to the constraints imposed by the expected degree sequence are studied. It is found that the linear preferential attachment is a fundamental rule, as it keeps the maximal entropy in sparse growing networks. This provides theoretical evidence in support of the linear preferential attachment widely exists in real networks and adopted as a crucial assumption in growing network models. Besides, in the sparse limit, we develop a method to calculate the degree correlation and clustering coefficient in our ensemble model, which is suitable for all kinds of sparse networks including the BA model, proposed by Barabási and Albert.

Keywords: Preferential attachment; Scale-free networks; Statistical mechanics of graph ensemble (search for similar items in EconPapers)
Date: 2005
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:356:y:2005:i:2:p:662-670

DOI: 10.1016/j.physa.2005.04.005

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