A study of rumor control strategies on social networks

2010 ◽  
Author(s):  
Rudra M. Tripathy ◽  
Amitabha Bagchi ◽  
Sameep Mehta
Keyword(s):  
Social Networks ◽  
Control Strategies ◽  
Rumor Control

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 A Bio-Inspired Defensive Rumor Confinement Strategy in Online Social Networks

2021 ◽  
Vol 33 (1) ◽  
pp. 47-70
Author(s):  
Santhoshkumar Srinivasan ◽  
Dhinesh Babu L. D.
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Propagation Model ◽  
Information Propagation ◽  
Control Approach ◽  
Rumor Propagation ◽  
Immunization Strategies ◽  
New Information ◽  
The Individual ◽  
Rumor Control

Online social networks (OSNs) are used to connect people and propagate information around the globe. Along with information propagation, rumors also penetrate across the OSNs in a massive order. Controlling the rumor propagation is utmost important to reduce the damage it causes to society. Educating the individual participants of OSNs is one of the effective ways to control the rumor faster. To educate people in OSNs, this paper proposes a defensive rumor control approach that spreads anti-rumors by the inspiration from the immunization strategies of social insects. In this approach, a new information propagation model is defined to study the defensive nature of true information against rumors. Then, an anti-rumor propagation method with a set of influential spreaders is employed to defend against the rumor. The proposed approach is compared with the existing rumor containment approaches and the results indicate that the proposed approach works well in controlling the rumors.

scholarly journals A Novel Method to Rank Influential Nodes in Complex Networks Based on Tsallis Entropy

Entropy ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. 848 ◽  
Author(s):  
Xuegong Chen ◽  
Jie Zhou ◽  
Zhifang Liao ◽  
Shengzong Liu ◽  
Yan Zhang
Keyword(s):  
Social Networks ◽  
Rapid Development ◽  
Entropy Method ◽  
Tsallis Entropy ◽  
Network Nodes ◽  
Related Research ◽  
Novel Method ◽  
Influential Nodes ◽  
Rumor Control ◽  
The Relationship

With the rapid development of social networks, it has become extremely important to evaluate the propagation capabilities of the nodes in a network. Related research has wide applications, such as in network monitoring and rumor control. However, the current research on the propagation ability of network nodes is mostly based on the analysis of the degree of nodes. The method is simple, but the effectiveness needs to be improved. Based on this problem, this paper proposes a method that is based on Tsallis entropy to detect the propagation ability of network nodes. This method comprehensively considers the relationship between a node’s Tsallis entropy and its neighbors, employs the Tsallis entropy method to construct the TsallisRank algorithm, and uses the SIR (Susceptible, Infectious, Recovered) model for verifying the correctness of the algorithm. The experimental results show that, in a real network, this method can effectively and accurately evaluate the propagation ability of network nodes.

scholarly journals Optimal Control of ISTR Rumor Propagation Model with Social Reinforcement in Heterogeneous Network

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Liang’an Huo ◽  
Sijing Chen ◽  
Xiaoxiao Xie ◽  
Huiyuan Liu ◽  
Jianjia He
Keyword(s):  
Optimal Control ◽  
Reproduction Number ◽  
Control Strategies ◽  
Minimum Principle ◽  
Optimal Solution ◽  
Propagation Model ◽  
Social Reinforcement ◽  
Social Stability ◽  
Rumor Propagation ◽  
Rumor Control

The wide spread of rumor is undoubtedly harmful to social stability; we should try to lower the effect of rumor on society. Therefore, it is reasonable to put forward the rumor control strategy on the basis of the study of the law of rumor propagation. Firstly, the ISTR model of rumor is established by including influencing factors of true information spreader and social reinforcement. And by using the next generation matrix method, the basic reproduction number of rumor is obtained. Then, in order to minimize the adverse effects of rumors, through introducing two control strategies of scientific knowledge popularization and refutation of rumors, the optimal control problem is established. And through using Pontryagin’s Minimum Principle, the optimal solution of the rumor propagation model is solved. Finally, through theoretical analysis and numerical simulation, some results can be obtained. The results show that adding true information spreaders into the rumor model can effectively control the rumor propagation, and social reinforcement plays a significance role in rumor. The results also prove that these two control strategies can effectively inhibit the propagation of rumors. With the addition of control strategies, the number of true information spreaders increases, while the number of rumor spreaders decreases.

scholarly journals Evolutionary information dynamics over social networks: a review

2020 ◽  
Vol 4 (1) ◽  
pp. 45-59
Author(s):  
Hangjing Zhang ◽  
Yan Chen ◽  
H. Vicky Zhao
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Evolutionary Game ◽  
Evolutionary Information ◽  
Stable States ◽  
Information Dynamics ◽  
Content Type ◽  
Rumor Control

Purpose The purpose of this paper is to have a review on the analysis of information diffusion based on evolutionary game theory. People now get used to interact over social networks, and one of the most important functions of social networks is information sharing. Understanding the mechanisms of the information diffusion over social networks is critical to various applications including online advertisement and rumor control. Design/methodology/approach It has been shown that the graphical evolutionary game theory (EGT) is a very efficient method to study this problem. Findings By applying EGT to information diffusion, the authors could predict every small change in the process, get the detailed dynamics and finally foretell the stable states. Originality/value In this paper, the authors provide a general review on the evolutionary game-theoretic framework for information diffusion over social network by summarizing the results and conclusions of works using graphical EGT.

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