Empirical analysis of the worldwide maritime transportation network

TL;DR

This paper empirically analyzes the worldwide maritime transportation network, revealing its small-world, hierarchical, and rich-club properties through various network topology measures.

Contribution

It provides a comprehensive empirical characterization of WMN's topology, including power law distributions and hierarchy, using multiple network representations.

Findings

WMN exhibits small-world and power law behavior

Identification of key nodes based on centrality measures

Revealed hierarchy and rich-club phenomena in WMN

Abstract

In this paper we present an empirical study of the worldwide maritime transportation network (WMN) in which the nodes are ports and links are container liners connecting the ports. Using the different representation of network topology namely the space $L$ and $P$, we study the statistical properties of WMN including degree distribution, degree correlations, weight distribution, strength distribution, average shortest path length, line length distribution and centrality measures. We find that WMN is a small-world network with power law behavior. Important nodes are identified based on different centrality measures. Through analyzing weighted cluster coefficient and weighted average nearest neighbors degree, we reveal the hierarchy structure and "rich-club" phenomenon in the network.