Memory effects induce structure in social networks with activity-driven agents

Activity-driven modelling has recently been proposed as an alternative growth mechanism for time varying networks,displaying power-law degree distribution in time-aggregated representation. This approach assumes memoryless agents developing random connections with total disregard of their previous c...

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Detalles Bibliográficos
Autores: Medus, A. D., Dorso, Claudio Oscar
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2014
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/17927
Acceso en línea:http://hdl.handle.net/11336/17927
Access Level:acceso abierto
Palabra clave:Stochastic Processes
Growth Processes
Network Dynamics
https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
Descripción
Sumario:Activity-driven modelling has recently been proposed as an alternative growth mechanism for time varying networks,displaying power-law degree distribution in time-aggregated representation. This approach assumes memoryless agents developing random connections with total disregard of their previous contacts. Thus, such an assumption leads to time-aggregated random networks that do not reproduce the positive degree-degree correlation and high clustering coefficient widely observed in real social networks. In this paper, we aim to study the incidence of the agents’ long-term memory on the emergence of new social ties. To this end, we propose a dynamical network model assuming heterogeneous activity for agents, together with a triadic-closure step as main connectivity mechanism. We show that this simple mechanism provides some of the fundamental topological features expected for real social networks in their time-aggregated picture. We derive analytical results and perform extensive numerical simulations in regimes with and without population growth. Finally, we present an illustrative comparison with two case studies, one comprising faceto-face encounters in a closed gathering, while the other one corresponding to social friendship ties from an online social network.