Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12779/6119
Title: Spatial effects in real networks: Measures, null models, and applications
Authors: Ruzzenenti, Franco
Picciolo, Francesco
Basosi, Riccardo 
Garlaschelli, Diego
Issue Date: 2012
Project: None 
Journal: PHYSICAL REVIEW E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS
Abstract: 
Spatially embedded networks are shaped by a combination of purely topological (space-independent) and space-dependent formation rules. While it is quite easy to artificially generate networks where the relative importance of these two factors can be varied arbitrarily, it is much more difficult to disentangle these two architectural effects in real networks. Here we propose a solution to this problem, by introducing global and local measures of spatial effects that, through a comparison with adequate null models, effectively filter out the spurious contribution of nonspatial constraints. Our filtering allows us to consistently compare different embedded networks or different historical snapshots of the same network. As a challenging application we analyze the World Trade Web, whose topology is known to depend on geographic distances but is also strongly determined by nonspatial constraints (degree sequence or gross domestic product). Remarkably, we are able to detect weak but significant spatial effects both locally and globally in the network, showing that our method succeeds in retrieving spatial information even when nonspatial factors dominate. We finally relate our results to the economic literature on gravity models and trade globalization
Description: 
67999
URI: http://hdl.handle.net/20.500.12779/6119
ISSN: 1539-3755
DOI: 10.1103/PhysRevE.86.066110
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