Stratified Configuration Model for Simulating Networks

Carlos Miguel Moreira Gonçalves (), Pablo Ignacio Fierens () and Leandro Rêgo ()
Additional contact information
Pablo Ignacio Fierens: https://www.itba.edu.ar/centros/cdo/laboratorio-de-optoelectronica/
Leandro Rêgo: https://sites.google.com/dema.ufc.br/leandro

Journal of Artificial Societies and Social Simulation, 2026, vol. 29, issue 2, 6

Abstract: Conventional network generation models exhibit limitations in capturing complex structural patterns influenced by nodal and link attributes. While recent models have partially addressed this issue, significant gaps persist. This work introduces an adaptation of the Configuration Model that incorporates nodal attributes as crucial factors in determining network structure. We implemented a modification in the generation process to increase the clustering coefficient and propose two distinct algorithms: one for scenarios where the complete network topology is known and another for situations of incomplete network information. We demonstrate that our methodology can replicate network topology with edge losses below 12%, results in up to a tenfold increase in the clustering coefficient, and faithfully reproduces link distributions among different nodal categories.

Keywords: Complex Networks; Stratified Networks; Configuration Model (search for similar items in EconPapers)
Date: 2026-03-31
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.jasss.org/29/2/6/6.pdf (application/pdf)

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:jas:jasssj:2025-90-3

Access Statistics for this article

More articles in Journal of Artificial Societies and Social Simulation from Journal of Artificial Societies and Social Simulation
Bibliographic data for series maintained by Francesco Renzini ().