Scale-Free Networks Generated By Random Walkers

TL;DR

This paper introduces a simple method for generating scale-free networks using random walks, resulting in networks with a degree exponent of 3 and variable clustering, offering a new perspective on preferential attachment.

Contribution

The paper presents a novel mechanism for creating scale-free networks via random walks, avoiding explicit degree knowledge and reproducing key network properties.

Findings

Produces scale-free networks with gamma=3

Clustering coefficients depend on walk length

Mechanism mimics preferential attachment without explicit degree info

Abstract

We present a simple mechanism for generating undirected scale-free networks using random walkers, where the network growth is determined by choosing parent vertices by sequential random walks. We show that this mechanism produces scale-free networks with degree exponent gamma=3 and clustering coefficients depending on random walk length. The mechanism can be interpreted in terms of preferential attachment without explicit knowledge of node degrees.