scholarly journals Dynamical Analysis of an SE2IR Information Propagation Model in Social Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Qian Zhang ◽  
Xianyong Li ◽  
Yajun Du ◽  
Jian Zhu
Keyword(s):  
Social Network ◽  
Equilibrium Point ◽  
Control Strategies ◽  
Propagation Model ◽  
Dynamical Analysis ◽  
Information Control ◽  
Information Propagation ◽  
Real Process ◽  
The Social ◽  
Reinforcement Intensity

Due to the inequality of users’ (nodes’) status and the influence of external forces in the progress of the information propagation in a social network, the infected nodes hold different levels of propagation capacity. For this reason, the infected nodes are classified into two categories: the high influential infected nodes and the ordinary influential infected nodes which separately account for 20% and 80% by Pareto’s principle. By borrowing the SEIR epidemic model, this paper proposes an SE2IR information propagation model. Meanwhile, the global asymptotical stabilities of the spread-free equilibrium point and local spread equilibrium point are proved for this model. This paper also puts forward a series of information control strategies including perceived values of users, social reinforcement intensity, and information timeliness in the social network. Through simulation experiments without or with control strategies on a real company e-mail network dataset, this paper verifies the stability and correctness of the model and the feasibility and effectiveness of the control strategies in the information propagation process, presenting that the model is closer to the real process of the information propagation in the social network.

scholarly journals A Literature Review of Social Network Analysis in Epidemic Prevention and Control

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Xiaomei Wang ◽  
Qi An ◽  
Zilong He ◽  
Wei Fang
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Prevention And Control ◽  
Control Strategies ◽  
China National Knowledge Infrastructure ◽  
Comprehensive Overview ◽  
Knowledge Infrastructure ◽  
The Social ◽  
New Research ◽  
And Control

Studying the structure and evolution characteristics of social networks is of great significance in assessing and controlling the outbreak of infectious diseases. Therefore, it is necessary to find research trends in this field. In this study, 1,752 documents (2001–2020) related to the relationship between the social network and epidemic published from Scopus, WOS (Web of Science), and CNKI (China National Knowledge Infrastructure) databases were studied to provide a more comprehensive overview of the frontiers of research in this field, including epidemics in social networks, spread of disease, influence of different factors on the spread of the epidemic, prevention and control strategies of the epidemic, and comparison of various strategies. Besides, several new research directions in this field worthy of attention of researchers are discussed.

scholarly journals Detecting the Influencer on Social Networks Using Passion Point and Measures of Information Propagation †

2020 ◽  
Vol 12 (7) ◽  
pp. 3064 ◽  
Author(s):  
Tai Huynh ◽  
Hien Nguyen ◽  
Ivan Zelinka ◽  
Dac Dinh ◽  
Xuan Hau Pham
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Marketing Strategy ◽  
Online Social Network ◽  
Modern Method ◽  
Information Propagation ◽  
The Social ◽  
User Data ◽  
The Impact ◽  
Positive Results

Influencer marketing is a modern method that uses influential users to approach goal customers easily and quickly. An online social network is a useful platform to detect the most effective influencer for a brand. Thus, we have an issue: how can we extract user data to determine an influencer? In this paper, a model for representing a social network based on users, tags, and the relationships among them, called the SNet model, is presented. A graph-based approach for computing the impact of users and the speed of information propagation, and measuring the favorite brand of a user and sharing the similar brand characteristics, called a passion point, is proposed. Therefore, we consider two main influential measures, including the extent of the influence on other people by the relationships between users and the concern to user’s tags, and the tag propagation through social pulse on the social network. Based on these, the problem of determining the influencer of a specific brand on a social network is solved. The results of this method are used to run the influencer marketing strategy in practice and have obtained positive results.

scholarly journals Dynamical analysis and control strategies on malware propagation model

2013 ◽  
Vol 37 (16-17) ◽  
pp. 8225-8236 ◽  
Author(s):  
Liping Feng ◽  
Xiaofeng Liao ◽  
Qi Han ◽  
Huaqing Li
Keyword(s):  
Control Strategies ◽  
Propagation Model ◽  
Dynamical Analysis ◽  
Malware Propagation ◽  
And Control

scholarly journals Online Social Network Emergency Public Event Information Propagation and Nonlinear Mathematical Modeling

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Xiaoyang Liu ◽  
Chao Liu ◽  
Xiaoping Zeng
Keyword(s):  
Mathematical Modeling ◽  
Social Network ◽  
Dynamic Method ◽  
Online Social Network ◽  
Propagation Model ◽  
Information Propagation ◽  
Public Event ◽  
Network Nodes ◽  
Event Information ◽  
Simulation Results

Emergency public event arises everyday on social network. The information propagation of emergency public event (favorable and harmful) is researched. The dynamics of a susceptible-infected-susceptible and susceptible-infected-removed epidemic models incorporated with information propagation of emergency public event are studied. In particular, we investigate the propagation model and the infection spreading pattern using nonlinear dynamic method and results obtained through extensive numerical simulations. We further generalize the model for any arbitrary number of infective network nodes to mimic existing scenarios in online social network. The simulation results reveal that the inclusion of multiple infective node achieved stability and equilibrium in the proposed information propagation model.

Social network information propagation model based on individual behavior

2017 ◽  
Vol 14 (7) ◽  
pp. 1-15 ◽  
Author(s):  
Lejun Zhang ◽  
Hongjie Li ◽  
Chunhui Zhao ◽  
Xiaoying Lei
Keyword(s):  
Social Network ◽  
Individual Behavior ◽  
Propagation Model ◽  
Information Propagation ◽  
Network Information ◽  
Model Based
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