pith. sign in

arxiv: 2101.05389 · v1 · pith:KVH5XTCNnew · submitted 2021-01-13 · 📊 stat.AP

Assortativity measures for weighted and directed networks

classification 📊 stat.AP
keywords assortativitymeasuresnetworkscoefficientsdirectedexistingfeaturesmeasure
0
0 comments X
read the original abstract

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 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".

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.