Autor según el artículo: Granell, Clara; Darst, Richard K; Arenas, Alex; Fortunato, Santo; Gomez, Sergio
Departamento: Enginyeria Informàtica i Matemàtiques
Autor/es de la URV: Arenas Moreno, Alejandro / Gómez Jiménez, Sergio / Granell Martorell, Clara
Palabras clave: Stochastic systems Stochastic models Stochastic block models Social sciences Short time windows Population dynamics Periodic oscillation Evolving networks Dynamic scenarios Computer networks Complex networks Community structures Community detection Benchmark models
Resumen: Detecting the time evolution of the community structure of networks is crucial to identify major changes in the internal organization of many complex systems, which may undergo important endogenous or exogenous events. This analysis can be done in two ways: considering each snapshot as an independent community detection problem or taking into account the whole evolution of the network. In the first case, one can apply static methods on the temporal snapshots, which correspond to configurations of the system in short time windows, and match afterward the communities across layers. Alternatively, one can develop dedicated dynamic procedures so that multiple snapshots are simultaneously taken into account while detecting communities, which allows us to keep memory of the flow. To check how well a method of any kind could capture the evolution of communities, suitable benchmarks are needed. Here we propose a model for generating simple dynamic benchmark graphs, based on stochastic block models. In them, the time evolution consists of a periodic oscillation of the system's structure between configurations with built-in community structure. We also propose the extension of quality comparison indices to the dynamic scenario. © 2015 American Physical Society.
Áreas temáticas: Zootecnia / recursos pesqueiros Statistics and probability Statistical and nonlinear physics Saúde coletiva Química Physics, mathematical Physics, fluids & plasmas Odontología Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Interdisciplinar Geociências General medicine Farmacia Engenharias iv Engenharias iii Engenharias ii Educação física Educação Economia Condensed matter physics Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência da computação Biotecnología Biodiversidade Astronomia / física
Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
Direcció de correo del autor: clara.granell@urv.cat sergio.gomez@urv.cat alexandre.arenas@urv.cat
Identificador del autor: 0000-0003-1820-0062 0000-0003-0937-0334
Fecha de alta del registro: 2024-09-28
Versión del articulo depositado: info:eu-repo/semantics/acceptedVersion
Enlace a la fuente original: https://journals.aps.org/pre/abstract/10.1103/PhysRevE.92.012805
URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
Referencia al articulo segun fuente origial: Physical Review e. 92 (1): 012805-
Referencia de l'ítem segons les normes APA: Granell, Clara; Darst, Richard K; Arenas, Alex; Fortunato, Santo; Gomez, Sergio (2015). Benchmark model to assess community structure in evolving networks. Physical Review e, 92(1), 012805-. DOI: 10.1103/PhysRevE.92.012805
DOI del artículo: 10.1103/PhysRevE.92.012805
Entidad: Universitat Rovira i Virgili
Año de publicación de la revista: 2015
Tipo de publicación: Journal Publications