The bass diffusion model: agent-based implementation on arbitrary networks

Autor: L. Di Lucchio, G. Modanese
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Mathematical and Computer Modelling of Dynamical Systems, Vol 30, Iss 1, Pp 364-384 (2024)
Druh dokumentu: article
ISSN: 13873954
1744-5051
1387-3954
DOI: 10.1080/13873954.2024.2350244
Popis: The goal of this study is to model Bass diffusion and its extensions on complex networks, including scale-free networks with arbitrary power-law exponent and assortative degree correlations. For this purpose we employ a combination of the free software packages networkX and NetLogo. Some new results obtained in the agent-based simulations (and differing from those in mean-field approximation) are the following. The introduction of assortative correlations in scale-free networks has the effect of delaying the adoption peak in the Bass model, compared to the uncorrelated case. The peak time depends strongly also on the maximum degree effectively present in the network. For diffusion models with threshold on signed network, a high level of clustering tends to cause adoption blockades. By analysing statistical ensembles of assortative networks generated via Newman rewiring one observes a remarkable strong correlation between the average degree of first neighbours [Formula: see text] and the average clustering coefficient [Formula: see text].
Databáze: Directory of Open Access Journals
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