Microscopic generative models for complex networks

Abstract

Over the last decade there has been growing interest in the understanding of complex networks such as the Internet, the World Wide Web and social networks. A large part of the research in this area has focused on macroscopic properties and models for complex networks such as the power law distribution of edge degrees and the small world phenomenon. Less attention has been paid to microscopic properties and models that try to model and explain the interaction and dynamics between individual vertices in a network. In this paper we discuss why such microscopic models play an important part in understanding complex networks. In particular we present examples of how microscopic generative models can be used to design efficient algorithms for complex networks.