scholarly journals An information spreading model based on relative weight in social network

2015 ◽  
Vol 64 (5) ◽  
pp. 050501
Author(s):  
Wang Jin-Long ◽  
Liu Fang-Ai ◽  
Zhu Zhen-Fang
Keyword(s):  
Social Network ◽  
Relative Weight ◽  
Spreading Model ◽  
Model Based ◽  
Information Spreading

scholarly journals Link creation and information spreading over social and communication ties in an interest-based online social network

2012 ◽  
Vol 1 (1) ◽  
Author(s):  
Luca Maria Aiello ◽  
Alain Barrat ◽  
Ciro Cattuto ◽  
Rossano Schifanella ◽  
Giancarlo Ruffo
Keyword(s):  
Social Network ◽  
Online Social Network ◽  
Information Spreading

scholarly journals Improved SIR Advertising Spreading Model and Its Effectiveness in Social Network

2018 ◽  
Vol 129 ◽  
pp. 215-218 ◽  
Author(s):  
Yi Jing ◽  
Liu Peiyu ◽  
Tang Xiaobing ◽  
Liu Wenfeng
Keyword(s):  
Social Network ◽  
Spreading Model

scholarly journals Dynamics of an Information Spreading Model with Isolation

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Xia-Xia Zhao ◽  
Jian-Zhong Wang
Keyword(s):  
Mathematical Model ◽  
Hopf Bifurcation ◽  
Limit Cycle ◽  
Real World ◽  
Modern Society ◽  
The Real ◽  
Spreading Model ◽  
Wide Range ◽  
Bistable Phenomenon ◽  
Information Spreading

Information plays an important role in modern society. In this paper, we presented a mathematical model of information spreading with isolation. It was found that such a model has rich dynamics including Hopf bifurcation. The results showed that, for a wide range of parameters, there is a bistable phenomenon in the process of information spreading and thus the information cannot be well controlled. Moreover, the model has a limit cycle which implies that the information exhibits periodic outbreak which is consistent with the observations in the real world.

scholarly journals Identifying the Influential Latent Edges for Promoting the Co-SIR Model

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Dan Yang ◽  
Liming Pan ◽  
Zhidan Zhao ◽  
Tao Zhou
Keyword(s):  
Real World ◽  
Message Passing ◽  
Sir Model ◽  
Research Area ◽  
Disease Outbreak ◽  
Limited Attention ◽  
Original Network ◽  
Spreading Model ◽  
Spreading Dynamics ◽  
Information Spreading

The network-based cooperative information spreading is a widely existing phenomenon in the real world. For instance, the spreading of disease outbreak news and disease prevention information often coexist and interact with each other on the Internet. Promoting the cooperative spreading of information in network-based systems is a subject of great importance in both theoretical and practical perspectives. However, very limited attention has been paid to this specific research area so far. In this study, we propose an effective approach for identifying the influential latent edges (that is, the edges that do not originally exist) which, if added to the original network, can promote the cooperative susceptible-infected-recovered (co-SIR) dynamics. To be specific, we first obtain the probabilities of each nodes being in different node states by the message-passing approach. Then, based on the state probabilities of nodes obtained, we come up with an indicator, which incorporates both the information of network topology and the co-SIR dynamics, to measure the influence of each latent edge in promoting the co-SIR dynamics. Thus, the most influential latent edges can be located after ranking all the latent edges according to their quantified influence. We verify the rationality and superiority of the proposed indicator in identifying the influential latent edges of both synthetic and real-world networks by extensive numerical simulations. This study provides an effective approach to identify the influential latent edges for promoting the network-based co-SIR information spreading model and offers inspirations for further research on intervening the cooperative spreading dynamics from the perspective of performing network structural perturbations.

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