Visualisation and Analysis of Large and Complex Scale-free Networks

Abstract

Scale-free networks appear in many application domains such as social and biological networks [BA99, BB03, BO04]. Roughly speaking, scale-free networks have power-law degree distribution, ultra-short average path length and high clustering coefficient [BA99, BB03, BO04]. This paper presents new methods for visualising scale-free networks in three dimensions. To make effective use of the third dimension and minimise occlusion, we produce graph visulaisations with nodes constrained to lie on parallel planes or on the surface of spheres. We implement the algorithms using a variation of a fast force-directed graph layout method [QE00]. Results with real world data sets such as IEEE InfoVis citation and collaboration networks and a protein-protein interaction network show that our method can be useful for visual analysis of large and complex scale-free networks. We also discuss the issue of visualisation of evolving networks and network integration.