title: Temporal effects in the growth of networks.
abstract: We show that to explain the growth of the citation network by preferential attachment (PA), one has to accept that individual nodes exhibit heterogeneous fitness values that decay with time. While previous PA-based models assumed either heterogeneity or decay in isolation, we propose a simple analytically treatable model that combines these two factors. Depending on the input assumptions, the resulting degree distribution shows an exponential, log-normal or power-law decay, which makes the model an apt candidate for modeling a wide range of real systems.
authors.affiliation: Physics Department, University of Fribourg, CH-1700 Fribourg, Switzerland.
authors.forename: Matúš
authors.initials: M
authors.lastname: Medo
authors.forename: Giulio
authors.initials: G
authors.lastname: Cimini
authors.forename: Stanislao
authors.initials: S
authors.lastname: Gualdi
mesh_terms: D008962:Models, Theoretical; D013997:Time Factors