A Scale-Free Network Evolution Model Based on the Growth Characteristics of Social Networks

Abstract

In this paper, based on the classic BA scale-free network model, we proposed a new evolution model that gives a more realistic description \u00a0of the people\u2019s behavior on social networks. In the process of growth, there are local preferential attachment mechanisms and random attachment or removal between the old \u00a0and \u00a0new \u00a0edges. \u00a0We \u00a0proved \u00a0that \u00a0the \u00a0extended \u00a0model \u00a0follows \u00a0the \u00a0power-law \u00a0distribution \u00a0and \u00a0the \u00a0power exponent is between 2 and 3, which provides a theoretical support for analyzing the similar social network. Compared \u00a0with \u00a0the \u00a0classic \u00a0BA \u00a0model, \u00a0the \u00a0extended \u00a0model \u00a0has \u00a0a \u00a0smaller \u00a0average \u00a0path \u00a0length \u00a0and \u00a0a \u00a0larger clustering coefficient, which is more consistent with the real social network.