A general model for collaboration networks

TL;DR

This paper introduces a versatile model for collaboration networks that captures various degree distributions, exhibits small-world properties, and naturally reproduces observed peak act-size distributions in empirical data.

Contribution

The paper presents a unified model with a single parameter that interpolates between different network types and explains empirical peak act-size distributions.

Findings

Model reproduces scale-free and exponential degree distributions.

Networks exhibit small-world characteristics.

Peak act-size distribution matches empirical observations.

Abstract

In this paper, we propose a general model for collaboration networks. Depending on a single free parameter "{\bf preferential exponent}", this model interpolates between networks with a scale-free and an exponential degree distribution. The degree distribution in the present networks can be roughly classified into four patterns, all of which are observed in empirical data. And this model exhibits small-world effect, which means the corresponding networks are of very short average distance and highly large clustering coefficient. More interesting, we find a peak distribution of act-size from empirical data which has not been emphasized before of some collaboration networks. Our model can produce the peak act-size distribution naturally that agrees with the empirical data well.