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SOE: Fachverband Physik sozio-ökonomischer Systeme
SOE 15: Poster Session
SOE 15.10: Poster
Mittwoch, 28. März 2012, 16:50–17:50, Poster F
Node weighted measures for complex interacting networks — Marc Wiedermann1,2, •Jonathan F. Donges1,2, Jobst Heitzig1, and Jürgen Kurths1,2 — 1Potsdam Institute for Climate Impact Research, Potsdam, Germany — 2Department of Physics, Humboldt University, Berlin, Germany
When network theory is used in the study of complex systems, the typically finite set of nodes of the network of interest is frequently either explicitly or implicitly considered representative of a much larger finite or infinite set of objects of interest. The selection procedure, e.g., formation of a subset or some kind of discretization or aggregation, typically results in individual nodes of the studied network representing quite differently sized regions of the domain of interest. This heterogenous sampling may induce substantial biases in derived network statistics. Examples are among others frequently studied spatially embedded networks, where nodes may represent differently sized areas or volumes, or trade networks, where nodes stand for economies of widely varying gross domestic product (GDP). To avoid these problems, we propose an axiomatic scheme based on the idea of node splitting invariance to derive consistently weighted variants of various commonly used statistical network measures which approximate the corresponding properties of the underlying domain of interest. We show that these measures can be generalized to study the topology of complex interacting networks and demonstrate their applicability to several real world networks.