A centrality measure for quantifying spread on weighted, directed networks

Christian G. Fink, Kelly Fullin, Guillermo Gutierrez, Nathan Omodt, Sydney Zinnecker, Gina Sprint and Sean McCulloch

Physica A: Statistical Mechanics and its Applications, 2023, vol. 626, issue C

Abstract: While many centrality measures for complex networks have been proposed, relatively few have been developed specifically for weighted, directed (WD) networks. Here we propose a centrality measure (Viral Centrality) for spread (of information, pathogens, etc.) through WD networks based on the independent cascade model (ICM). While calculating the most accurate results for the ICM generally requires Monte Carlo simulations, we show that Viral Centrality provides excellent approximation to ICM results for networks in which the weighted strength of cycles is not too large. We show this can be quantified with the leading eigenvalue of the weighted adjacency matrix, and we show that Viral Centrality outperforms other common centrality measures in both simulated and empirical WD networks. A Python implementation of the Viral Centrality algorithm has been made available at the Stanford Network Analysis Project repository.

Keywords: Network centrality; Weighted directed network; Independent cascade model (ICM); Susceptible infected recovered (SIR) model (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437123006386
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:626:y:2023:i:c:s0378437123006386

DOI: 10.1016/j.physa.2023.129083

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 ().