2017/12/15 by Sobolevsky, Stanislav
#05C82 #05C85 #91D30 #92C42 #FOS: Computer and information sciences #FOS: Physical sciences #G.2.2 #I.5.3 #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI)
paper · doi:10.48550/arxiv.1712.05792
Our recent paper [Grauwin et al. Sci. Rep. 7 (2017)] demonstrates that community and hierarchical structure of the networks of human interactions largely determines the least and should be taken into account while modeling them. In the present proof-of-concept pre-print the opposite question is considered: could the hierarchical structure itself be inferred to be best aligned with the network model? The inference mechanism is provided for both - spatial networks as well as complex networks in general - through a model based on hierarchical and (if defined) geographical distances. The mechanism allows to discover hierarchical and community structure at any desired resolution in complex networks and in particular - the space-independent structure of the spatial networks. The approach is illustrated on the example of the interstate people migration network in USA.