Multilayer network science: theory, methods, and applications
Resumen: Multilayer network science has emerged as a central framework for analysing interconnected and interdependent complex systems. Its relevance has grown substantially with the increasing availability of rich, heterogeneous data, which makes it possible to uncover and exploit the inherently multilayered organisation of many real-world networks. In this review, we summarise recent developments in the field. On the theoretical and methodological front, we outline core concepts and survey advances in community detection, dynamical processes, temporal networks, higher-order interactions, and machine-learning-based approaches. On the application side, we discuss progress across diverse domains, including interdependent infrastructures, spreading dynamics, computational social science, economic and financial systems, ecological and climate networks, science-of-science studies, network medicine, and network neuroscience. We conclude with a forward-looking perspective, emphasizing the need for standardised datasets and software, deeper integration of temporal and higher-order structures, and a transition toward genuinely predictive models of complex systems.
Idioma: Inglés
DOI: 10.1093/comnet/cnag007
Año: 2026
Publicado en: JOURNAL OF COMPLEX NETWORKS 14, 2 (2026), [42 pp.]
ISSN: 2051-1310

Financiación: info:eu-repo/grantAgreement/ES/DGA/E36-23R-FENOL
Financiación: info:eu-repo/grantAgreement/ES/MICINN/RYC2021-033226-I
Financiación: info:eu-repo/grantAgreement/ES/MICIU/PID2023-149409NB-I00
Tipo y forma: Artículo (Versión definitiva)
Área (Departamento): Área Física Teórica (Dpto. Física Teórica)

Derechos Reservados Derechos reservados por el editor de la revista


Exportado de SIDERAL (2026-05-06-13:58:41)


Visitas y descargas

Este artículo se encuentra en las siguientes colecciones:
Artículos > Artículos por área > Física Teórica



 Registro creado el 2026-05-06, última modificación el 2026-05-06


Versión publicada:
 PDF
Valore este documento:

Rate this document:
1
2
3
 
(Sin ninguna reseña)