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Abstract:

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 face-to-face encounters in a closed gathering, while the other one corresponding to social friendship ties from an online social network. © 2014 IOP Publishing Ltd and SISSA Medialab srl.

Registro:

Documento: Artículo
Título:Memory effects induce structure in social networks with activity-driven agents
Autor:Medus, A.D.; Dorso, C.O.
Filiación:Departamento de Física, Facultad de Ciencias Exactas Y Naturales, Universidad de Buenos Aires, Ciudad Autónoma de Buenos Aires, 1428, Argentina
Palabras clave:analysis of algorithms; growth processes; network dynamics; stochastic processes (theory)
Año:2014
Volumen:2014
Número:9
DOI: http://dx.doi.org/10.1088/1742-5468/2014/09/P09009
Título revista:Journal of Statistical Mechanics: Theory and Experiment
Título revista abreviado:J. Stat. Mech. Theory Exp.
ISSN:17425468
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_17425468_v2014_n9_p_Medus

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Citas:

---------- APA ----------
Medus, A.D. & Dorso, C.O. (2014) . Memory effects induce structure in social networks with activity-driven agents. Journal of Statistical Mechanics: Theory and Experiment, 2014(9).
http://dx.doi.org/10.1088/1742-5468/2014/09/P09009
---------- CHICAGO ----------
Medus, A.D., Dorso, C.O. "Memory effects induce structure in social networks with activity-driven agents" . Journal of Statistical Mechanics: Theory and Experiment 2014, no. 9 (2014).
http://dx.doi.org/10.1088/1742-5468/2014/09/P09009
---------- MLA ----------
Medus, A.D., Dorso, C.O. "Memory effects induce structure in social networks with activity-driven agents" . Journal of Statistical Mechanics: Theory and Experiment, vol. 2014, no. 9, 2014.
http://dx.doi.org/10.1088/1742-5468/2014/09/P09009
---------- VANCOUVER ----------
Medus, A.D., Dorso, C.O. Memory effects induce structure in social networks with activity-driven agents. J. Stat. Mech. Theory Exp. 2014;2014(9).
http://dx.doi.org/10.1088/1742-5468/2014/09/P09009