Incomplete information in scale-free networks

TL;DR

This paper introduces the first models of scale-free networks that account for incomplete information, analytically demonstrating that such networks can still exhibit scale-free properties with varying exponents, supported by simulation results.

Contribution

It proposes and analytically solves two models of scale-free networks under incomplete information, showing scale invariance persists without breakdown.

Findings

Scaling exponent varies with model parameters

Scale-free behavior persists despite incomplete information

Simulation results agree with analytical models

Abstract

We investigate the effect of incomplete information on the growth process of scale-free networks - a situation that occurs frequently e.g. in real existing citation networks. Two models are proposed and solved analytically for the scaling behavior of the connectivity distribution. These models show a varying scaling exponent with respect to the model parameters but no break-down of scaling thus introducing the first models of scale-free networks in an environment of incomplete information. We compare to results from computer simulations which show a very good agreement.