Promoting spreading dynamics in networked systems is of both theoretical and practical importance . In this study, we propose an effective edge-based strategy to promote the spreading dynamics of the susceptible-infected-recovered model on complex networks by adding latent edges (that is, edges that do not exist before) to the networks. Specifically, we first quantify the influence of each latent edge by a mathematical model. Then, we strategically add the latent edges to the original networks according to the  influence of each latent edge. The result of numerical simulations verifies the effectiveness of our strategy and demonstrates that our strategy outperforms certain static strategies, namely, adding the latent edges between nodes with the largest degree or eigenvector centrality. This study fills up the research blankness of promoting the SIR spreading dynamics by structural perturbations to some extent . Besides, the theoretical framework established in this study provides inspirations for the further investigations of edge-based promoting strategies for other spreading models.
Promoting some typical spreading dynamics, for instance, the spreading of information, commercial message, vaccination guidance, innovation, and political movement, can bring benefits to all aspects of the socio-economic systems . In this study, we propose a strategy for promoting the spreading of the susceptible-infected-recovered model , which is widely applied to describe these common spreading dynamics in real life. Specifically, we first quantify the potential influence that the addition of each latent edge (that is, edges that do not exist before) could cause to the spreading dynamics. Then, we strategically add the latent edges to the original networks according to the potential influence of each latent edge. Numerical simulations verify the effectiveness of our strategy and demonstrate that our strategy outperforms several static strategies, namely, adding the latent edges between nodes with the largest degree or eigenvector centrality. This study provides an effective way of promoting the spreading of the susceptible-infected-recovered model by modifying the network structure slightly and helps in understanding what a better network structure for the spreading dynamics is . Besides, the theoretical framework established in this study provides inspirations for the further investigations of edge-based promoting strategies for other spreading models.
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spreading dynamics in networked systems is of both theoretical and practical importance
some typical spreading dynamics, for instance, the spreading of information, commercial message, vaccination guidance, innovation, and political movement, can bring benefits to all aspects of the socio-economic systems
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an effective edge-based strategy to promote the spreading dynamics
a strategy for promoting the spreading
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on complex networks by adding latent edges
, which is widely applied to describe these common spreading dynamics in real life. Specifically, we first quantify the potential influence that the addition of each latent edge
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to the networks. Specifically, we first quantify the influence of each latent edge by a mathematical model.
could cause to the spreading dynamics.
A
potential
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The result of numerical simulations verifies
Numerical simulations verify
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demonstrates
demonstrate
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certain
several
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fills up the research blankness
provides an effective way
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SIR spreading dynamics by structural perturbations to some extent
spreading of the susceptible-infected-recovered model by modifying the network structure slightly and helps in understanding what a better network structure for the spreading dynamics is