This paper presents a new measure (the diffusion delay centrality—DDC) to identify agents who should be put into isolation to decelerate a diffusion process spreading throughout a network. We show that DDC assigns a high rank to agents acting as the gatekeepers of the fringe of the network. We also show that the ranking of nodes obtained from the DDC is predicted by the difference in the values of betweenness and eigenvector centrality of network agents. The findings presented might constitute a useful tool to reduce diffusion processes both for policy makers and for corporate managers in the organization of production.
Diffusion delay centrality: decelerating diffusion processes across networks
Leone Sciabolazza, Valerio;Riccetti, Luca
2022-01-01
Abstract
This paper presents a new measure (the diffusion delay centrality—DDC) to identify agents who should be put into isolation to decelerate a diffusion process spreading throughout a network. We show that DDC assigns a high rank to agents acting as the gatekeepers of the fringe of the network. We also show that the ranking of nodes obtained from the DDC is predicted by the difference in the values of betweenness and eigenvector centrality of network agents. The findings presented might constitute a useful tool to reduce diffusion processes both for policy makers and for corporate managers in the organization of production.File | Dimensione | Formato | |
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Descrizione: Diffusion delay centrality - ICC 2022.pdf
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