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Publisher: American Physical Society
Languages: English
Types: Article
Subjects: Computer Science - Social and Information Networks, Quantitative Biology - Populations and Evolution, Physics - Physics and Society
The vast majority of strategies aimed at controlling contagion processes on networks considers the connectivity pattern of the system as either quenched or annealed. However, in the real world many networks are highly dynamical and evolve in time concurrently to the contagion process. Here, we derive an analytical framework for the study of control strategies specifically devised for time-varying networks. We consider the removal/immunization of individual nodes according the their activity in the network and develop a block variable mean-field approach that allows the derivation of the equations describing the evolution of the contagion process concurrently to the network dynamic. We derive the critical immunization threshold and assess the effectiveness of the control strategies. Finally, we validate the theoretical picture by simulating numerically the information spreading process and control strategies in both synthetic networks and a large-scale, real-world mobile telephone call dataset
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    • [44] In order to guarantee that a fraction w of nodes is immunized/removed the systems need to be observed for more than one time step. We define T as the average time needed for all the probes to have at least one interaction with other nodes. For any observation time T < T the fraction of immunized/removed nodes will be in general p w.
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