Node-weighted interacting network measures improve the representation of real-world complex systems

2013/01/04 by Marc Wiedermann, M. Wiedermann, J. F. Donges +5 · 1 citation
Computer Science · Economics, Econometrics and Finance · Physics and Astronomy · #Class (philosophy) #Complex Network Analysis Techniques #Complex Systems and Time Series Analysis #Complex network #Complex system #Economic and Technological Innovation #Interdependence #Interdependent networks #Network dynamics #Node (physics) #Representation (politics) #Toolbox #cs.SI #physics.data-an #physics.soc-ph

paper · pdf · doi:10.1209/0295-5075/102/28007

published as Europhysics Letters 102, 28007 (2013) · 7 pages, 5 figures

arxiv created 2013/01/04 · openalex publication_date 2013/04/01 · arxiv updated 2016/04/07 · openalex created_date 2016/06/24 · openalex updated_date 2026/08/05

Abstract

Many real-world complex systems are adequately represented by networks of interacting or interdependent networks. Additionally, it is often reasonable to take into account node weights such as surface area in climate networks, volume in brain networks, or economic capacity in trade networks to reflect the varying size or importance of subsystems. Combining both ideas, we derive a novel class of statistical measures for analysing the structure of networks of interacting networks with heterogeneous node weights. Using a prototypical spatial network model, we show that the newly introduced node-weighted interacting network measures provide an improved representation of the underlying system's properties as compared to their unweighted analogues. We apply our method to study the complex network structure of cross-boundary trade between European Union (EU) and non-EU countries finding that it provides relevant information on trade balance and economic robustness.

Citations

• Robustness of interdependent networks under targeted attack
• Catastrophic cascade of failures in interdependent networks
• The Product Space Conditions the Development of Nations
• What Do Networks Have to Do with Climate?
• Geometric detection of coupling directions by means of inter-system recurrence networks

Cited by

• Unified functional network and nonlinear time series analysis for complex systems science: Thepyunicornpackage

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