Rumor propagation range estimation method based on a social network double-rumor model

Abstract

The invention discloses a social network double-rumor model-based rumor propagation range estimation method, which comprises the following steps: according to an SI model, considering propagation of two rumor and interaction between the two rumor, constructing a double-rumor SI model, and obtaining a differential equation set of time-varying user number proportions in different states under the double-rumor SI model; on the basis of the SI model, considering the condition of an immunization person, constructing a double rumor model based on the SIR model, and respectively considering a degreeuniformity network and a degree nonuniformity network to obtain a differential equation set of time-varying user number proportions under the double rumor SIR model; and the equation is simplified, propagation threshold expressions in the two networks are derived, and the relationship between the propagation threshold and the propagation range in the final state steady state is obtained, so that the propagation range of the rumor is estimated. The method can be applied to finding appropriate time to control diffusion of the rumor under different network conditions, the influence of the rumor is reduced, the rumor propagation range can be estimated, and rumor propagation is effectively inhibited.

Description

technical field [0001] The invention relates to the field of information dissemination, in particular to a method for estimating the spread range of rumors in a social network. Background technique [0002] In the 1960s, Milgram first proposed the theory of six degrees of separation, which laid the theoretical foundation for the development of online social networks. The network science theory of social network research originates from the study of complex networks, and its related theories can be traced back to 1960. and the random graph model of ER proposed by Rényi. On this basis, research on complex networks has developed rapidly, and the most notable achievements are the small-world network model proposed by Watts et al. based on the nature of network clustering in 1998, and Barabési et al. The scale-free network model proposed by the and out-degree approximately obeying the power-law distribution. Since then, most scholars have revised and extended the models based...

AI Technical Summary

Problems solved by technology

However, there are still few studies on how two rumors can promote or inhibit each other when two rumors spread simultaneously on the Internet, and the accuracy of the estimation of the spread of rumors needs to be improved.

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