ANALYSIS OF RUMOR PROPAGATION DYNAMICS IN COMPLEX NETWORKS

Considering that rumors propagation is affected by many factors in real life, based on the SIRS infectious disease model in complex networks, an extended ISRI rumor propagation model is proposed by using the probability function to define the influence mechanisms such as trust mechanism, and suspicion mechanism. First, dynamic equations are established for homogeneous and heterogeneous networks, and the rumor and rumor-free equilibrium points in the two networks are analyzed, respectively. Then, the basic reproduction number [Formula: see text] is obtained by using the next generation matrix and derivative calculation methods. Next, the lyapunov function is constructed to discuss the local stability and global stability of the equilibrium point, and the influence of different parameters on the basic reproduction number [Formula: see text]. In addition, we selected ER network and BA network and found that population flow has a significant impact on the speed and scale of rumor propagation. At the same time, the trust mechanism can improve the propagation speed and scale, while the skepticism mechanism can inhibit the propagation speed, and it is more obvious in the BA network. The interaction between these mechanisms further affects the propagation characteristics of rumors in the network.

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Publication Details

Journal
Advances in Complex Systems
Published
2024-12-20
DOI
https://doi.org/10.1142/s0219525925500055
Citations
1
Primary Topic
Opinion Dynamics and Social Influence
Type
article
Field-Weighted Citation Impact
0.28
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article

ANALYSIS OF RUMOR PROPAGATION DYNAMICS IN COMPLEX NETWORKS

Wenwen Chang, Huayan Pei, Guanghui Yan, J. Tang
1 citations
Advances in Complex Systems
Opinion Dynamics and Social Influence
0.28
article

ANALYSIS OF RUMOR PROPAGATION DYNAMICS IN COMPLEX NETWORKS

Wenwen Chang, Huayan Pei, Guanghui Yan, J. Tang
article en
1 citations

Abstract

Considering that rumors propagation is affected by many factors in real life, based on the SIRS infectious disease model in complex networks, an extended ISRI rumor propagation model is proposed by using the probability function to define the influence mechanisms such as trust mechanism, and suspicion mechanism. First, dynamic equations are established for homogeneous and heterogeneous networks, and the rumor and rumor-free equilibrium points in the two networks are analyzed, respectively. Then, the basic reproduction number [Formula: see text] is obtained by using the next generation matrix and derivative calculation methods. Next, the lyapunov function is constructed to discuss the local stability and global stability of the equilibrium point, and the influence of different parameters on the basic reproduction number [Formula: see text]. In addition, we selected ER network and BA network and found that population flow has a significant impact on the speed and scale of rumor propagation. At the same time, the trust mechanism can improve the propagation speed and scale, while the skepticism mechanism can inhibit the propagation speed, and it is more obvious in the BA network. The interaction between these mechanisms further affects the propagation characteristics of rumors in the network.

Advances in Complex SystemsVol. 28(01n02)
Lanzhou Jiaotong University (CN)
Openalex Percentile: Top 42%
Opinion Dynamics and Social Influence
0.28
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