Interplay between epidemic and information spreading on multiplex networks

2021 ◽  
Vol 188 ◽  
pp. 268-279
Author(s):  
Linhe Zhu ◽  
Wenshan Liu ◽  
Zhengdi Zhang
2020 ◽  
Vol 102 (2) ◽  
Author(s):  
Fátima Velásquez-Rojas ◽  
Paulo Cesar Ventura ◽  
Colm Connaughton ◽  
Yamir Moreno ◽  
Francisco A. Rodrigues ◽  
...  

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 104316-104325
Author(s):  
Xiuli Yu ◽  
Qiwen Yang ◽  
Kailiang Ai ◽  
Xuzhen Zhu ◽  
Wei Wang

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Byungjoon Min ◽  
Sang-Hwan Gwak ◽  
Nanoom Lee ◽  
K. -I. Goh

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Xuzhen Zhu ◽  
Jinming Ma ◽  
Xin Su ◽  
Hui Tian ◽  
Wei Wang ◽  
...  

Information spreading on multiplex networks has been investigated widely. For multiplex networks, the relations of each layer possess different extents of intimacy, which can be described as weighted multiplex networks. Nevertheless, the effect of weighted multiplex network structures on information spreading has not been analyzed comprehensively. We herein propose an information spreading model on a weighted multiplex network. Then, we develop an edge-weight-based compartmental theory to describe the spreading dynamics. We discover that under any adoption threshold of two subnetworks, reducing weight distribution heterogeneity does not alter the growth pattern of the final adoption size versus information transmission probability while accelerating information spreading. For fixed weight distribution, the growth pattern changes with the heterogeneous of degree distribution. There is a critical initial seed size, below which no global information outbreak can occur. Extensive numerical simulations affirm that the theoretical predictions agree well with the numerical results.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Jian Wang ◽  
Xiaolin Qin ◽  
Hongying Fang

Virus and information spreading dynamics widely exist in complex systems. However, systematic study still lacks for the interacting spreading dynamics between the two types of dynamics. This paper proposes a mathematical model on multiplex networks, which considers the heterogeneous susceptibility and infectivity in two subnetworks. By using a heterogeneous mean-field theory, we studied the dynamic process and outbreak threshold of the system. Through extensive numerical simulations on artificial networks, we find that the virus’s spreading dynamics can be suppressed by increasing the information spreading probability, decreasing the protection power, or decreasing the susceptibility and infectivity.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xiang Li ◽  
Bocheng Hou

Coevolution spreading dynamics on complex networks is a hot topic, which attracts much attention in network science. This paper proposes a mathematical model to describe the two competing complex information spreading dynamics on multiplex networks. An individual can only accept one of the two pieces of information. A heterogeneous mean-field theory is developed to describe the spreading dynamics. We reveal different regions through Monte Carlo simulations of the competing complex information spreading dynamics: no global information, one information dominant, and two information coexistence. We finally find that the heterogeneity of the multiplex networks’ degree distributions does not qualitatively affect the results.


Author(s):  
Guanying Huo ◽  
Xin Jiang ◽  
Lili Ma ◽  
Quantong Guo ◽  
Yifang Ma ◽  
...  

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