Many complex systems can be represented as networks, and the problem of network comparison is becoming increasingly relevant. There are many techniques for network comparison, from simply comparing network summary statistics to sophisticated but computationally costly alignment-based approaches. Yet it still remains challenging to cluster correctly networks that are of a different size and density, but hypothesized to be structurally similar. We address this problem by introducing a new network comparison methodology that is aimed at identifying common organizational principles in networks. The methodology is simple, intuitive and applicable in a wide variety of settings ranging from the functional classification of proteins to tracking the evolution of the world trade network.
This is joint work with Anatol Wegner Luis Ospina-Forero, Charlotte Deane and Gesine Reinert.