Assortative mixing in weighted directed networks

U. Pigorsch and M. Sabek

Physica A: Statistical Mechanics and its Applications, 2022, vol. 604, issue C

Abstract: We analyse assortative mixing, the tendency of vertices to bond with others based on similarities (usually excess vertex degree), in weighted networks, both directed and undirected. We propose a generalisation of the concept of assortativity by introducing our generalised assortativity coefficient. We also provide procedures that allow for both precisely assessing and interpreting the assortativity of weighted networks as well as its statistical significance. Finally, we demonstrate the usefulness of our proposed generalised assortativity coefficient by in-depth analysing the assortativity structure of several weighted real-world networks.

Keywords: Assortativity; Network; Graph; Weighted assortativity coefficient; Excess strength (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437122005519
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:604:y:2022:i:c:s0378437122005519

DOI: 10.1016/j.physa.2022.127850

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().