Evolving Scale-Free Network Model with Tunable Clustering

Abstract

The Barab\'{a}si-Albert (BA) model is extended to include the concept of local world and the microscopic event of adding edges. With probability $p$, we add a new node with $m$ edges which preferentially link to the nodes presented in the network; with probability $1-p$, we add $m$ edges among the present nodes. A node is preferentially selected by its degree to add an edge randomly among its neighbors. Using continuum theory and rate equation method we get the analytical expressions of the power-law degree distribution with exponent $\gamma=3$ and the clustering coefficient $c(k)\sim k^{-1}+c$. The analytical expressions are in good agreement with the numerical calculations.