Assortativity measures for weighted and directed networks
Published in Journal of Complex Networks, 2021
Recommended citation: Yuan, Y., Yan, J. and Zhang, P. (2021). "Assortativity measures for weighted and directed networks." Journal of Complex Networks, 9(2), cnab017. https://doi.org/10.1093/comnet/cnab017
Assortativity measures the tendency of a vertex in a network being connected by other vertexes with respect to some vertex-specific features. Classical assortativity coefficients are defined for unweighted and undirected networks with respect to vertex degree. We propose a class of assortativity coefficients that capture the assortative characteristics and structure of weighted and directed networks more precisely. The vertex-to-vertex strength correlation is used as an example, but the proposed measure can be applied to any pair of vertex-specific features. The effectiveness of the proposed measure is assessed through extensive simulations based on prevalent random network models in comparison with existing assortativity measures. In application to World Input-Ouput Networks, the new measures reveal interesting insights that would not be obtained by using existing ones. An implementation is publicly available in a R package wdnet.