Evolution of the social network of scientific collaborations

TL;DR

This paper analyzes the evolution of scientific collaboration networks, revealing their scale-free nature, growth dynamics, and proposing a model to simulate their development over time.

Contribution

It provides empirical measurements of the evolving topology of co-authorship networks and introduces a simple model capturing their growth mechanisms.

Findings

The network is scale-free with preferential attachment.

Average degree increases over time, contrary to some models.

Node separation decreases as the network evolves.

Abstract

The co-authorship network of scientists represents a prototype of complex evolving networks. By mapping the electronic database containing all relevant journals in mathematics and neuro-science for an eight-year period (1991-98), we infer the dynamic and the structural mechanisms that govern the evolution and topology of this complex system. First, empirical measurements allow us to uncover the topological measures that characterize the network at a given moment, as well as the time evolution of these quantities. The results indicate that the network is scale-free, and that the network evolution is governed by preferential attachment, affecting both internal and external links. However, in contrast with most model predictions the average degree increases in time, and the node separation decreases. Second, we propose a simple model that captures the network's time evolution. Third, numerical simulations are used to uncover the behavior of quantities that could not be predicted analytically.