PageRank Induced Topology for Real-World Networks

Abstract

This article presents a stochastic method for studying the structure of large small worlds graphs. The principle of this method is to apply a PageRank-like importance algorithm, with a damping factor and an external importance source. By varying the source vector, one obtains a powerful graph visualization tool, which reveals the structural organization of small worlds graphs