Abstract: With a core-periphery structure of networks, core nodes are densely interconnected, peripheral nodes are connected to core nodes to different extents, and peripheral nodes are sparsely interconnected. Core-periphery structure composed of a single core and periphery has been identified for various networks. However, analogous to the observation that many empirical networks are composed of densely interconnected groups of nodes, i.e., communities, a network may be better regarded as a collection of multiple cores and peripheries. We propose a scalable algorithm to detect multiple non-overlapping groups of core-periphery structure in a network. We illustrate our algorithm using synthesised and empirical networks. For example, in a world-wide airport network, we find three major groups of airports corresponding to Europe, East Asia and the USA, and separation between international and domestic subnetworks of airports in some single countries such as Thailand and Philippines.

Biography: Naoki Masuda received his PhD in 1998 from the University of Tokyo. He worked as Lecturer and then Associate Professor at the University of Tokyo between 2006 and 2014. He moved to University of Bristol, Department of Engineering Mathematics as Senior Lecturer, March 2014. His main research interests are network science and neuroimaging data analysis (using networks and statistical physics). His other research interests include evolutionary games, computational social science and collective behaviour.