scholarly journals Rumor-Propagation Model with Consideration of Refutation Mechanism in Homogeneous Social Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Laijun Zhao ◽  
Xiaoli Wang ◽  
Jiajia Wang ◽  
Xiaoyan Qiu ◽  
Wanlin Xie
Keyword(s):  
Social Networks ◽  
Mean Field ◽  
Propagation Rate ◽  
Spreading Rate ◽  
Propagation Model ◽  
Critical Threshold ◽  
Field Equations ◽  
Rumor Propagation ◽  
Mean Field Equations ◽  
The Stability

In recent years, increasing attention has been paid to how to effectively manage rumor propagation. Based on previous studies of rumor propagation and some strategies used by the authorities to refute rumors and manage rumor propagation, we develop a new rumor-propagation model with consideration of refutation mechanism. In this paper, we describe the dynamic process of rumor propagation by accounting for the refutation mechanism in homogeneous social networks. And then, we derive mean-field equations for rumor-propagation process. We then analyze the stability of the model with respect to changes in parameter values. Our results show that there exists a critical thresholdλcthat is inversely proportional to the average degree of the social networks and is positively correlated with the strength of the refutation mechanism. If the spreading rate is bigger than the critical thresholdλc, rumors can be spread. Our numerical simulations in homogeneous networks demonstrate that increasing the ignorant’s refutation rateβcan reduce the peak value of spreaders density, which is better than increasing the spreader’s refutation rateη. Therefore, based on the seriousness of the rumor propagation and the rumor-propagation rate, the authorities can choose effective strategies that increase the refutation rate so that they can reduce the maximum influence of the rumor.

Correlation and trust mechanisms-based rumor propagation model in complex social networks

2021 ◽  
Author(s):  
Xian-Li Sun ◽  
You-Guo Wang ◽  
Lin-Qing Cang
Keyword(s):  
Mean Field ◽  
Real Life ◽  
Propagation Model ◽  
Field Equations ◽  
Trust Mechanism ◽  
Rumor Propagation ◽  
Terminal Time ◽  
Immunization Strategies ◽  
Mean Field Equations ◽  
Theoretical Results

Abstract In real life, the process of rumor propagation is influenced by many factors. The complexity and uncertainty of human psychology make the diffusion model more challenging to depict. In order to establish a comprehensive propagation model, in this paper, we take some psychological factors into consideration to mirror rumor propagation. Firstly, we use the Ridenour model to combine the trust mechanism with the correlation mechanism and propose a modified rumor propagation model. Secondly, mean-field equations which describe the dynamics of the modified SIR model on homogenous and heterogeneous networks are derived. Thirdly, a steady-state analysis is conducted for the spreading threshold and the final rumor size. Fourthly, we investigate rumor immunization strategies and obtain immunization thresholds. Next, simulations on different networks are carried out to verify the theoretical results and the effectiveness of the immunization strategies. The results indicate that the utilization of trust and correlation mechanisms leads to a larger final rumor size and a smaller terminal time. Moreover, different immunization strategies have disparate effectiveness in rumor propagation.

scholarly journals C-SIW Rumor Propagation Model with Variable Propagation Rate and Perception Mechanism in Social Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Liqing Qiu ◽  
Shuqi Liu
Keyword(s):  
Social Networks ◽  
Propagation Rate ◽  
Propagation Model ◽  
Experimental Simulation ◽  
Field Equations ◽  
Dynamic Propagation ◽  
Rumor Propagation ◽  
Key Points ◽  
State Changes ◽  
The Individual

The propagation of rumor has become a common phenomenon in social networks. Studying the dynamic propagation of rumor can help locate the key points to control rumor propagation. To further research the internal motivation of state transition, a corrector-ignorant-spreader-weakener (C-SIW) model is proposed in this paper. When the individual changes state to transmit rumor, the neighbor may have a significant impact on rumor propagation. Considering the point, this paper constructs a function to describe the propagation rate, which relates to the state of neighbors and the reputation of the spreader. In addition, perception from life also can cause individual state changes. Based on the above fact, the links from the spreader and the weakener to the corrector are added to describe the perception mechanism. Then, combining the derived average field equations, the steady state of the model is analyzed and verified in experimental simulation. Moreover, the experimental results on different networks show that the perception mechanism reduces the rumor influence. Besides, the variable propagation rate can position the fast-growing stage of rumor propagation more accurately and facilitate the control of rumor propagation.

Modeling rumor propagation and refutation with time effect in online social networks

2018 ◽  
Vol 29 (08) ◽  
pp. 1850068 ◽  
Author(s):  
Yaming Zhang ◽  
Yanyuan Su ◽  
Weigang Li ◽  
Haiou Liu
Keyword(s):  
Social Networks ◽  
Heterogeneous Networks ◽  
Online Social Networks ◽  
Negative Impact ◽  
Time Effect ◽  
Field Equations ◽  
Two Stage ◽  
Dynamical Mechanism ◽  
Rumor Propagation ◽  
Mean Field Equations

Rumor propagation and refutation form an important issue for spreading dynamics in online social networks (OSNs). In this paper, we introduce a novel two-stage rumor propagation and refutation model with time effect for OSNs. The dynamical mechanism of rumor propagation and refutation with time effect is investigated deeply. Then a two-stage model and the corresponding mean-field equations in both homogeneous and heterogeneous networks are obtained. Monte Carlo simulations are conducted to characterize the dynamics of rumor propagation and refutation in both Watts–Strogatz network and Barabási–Albert network. The results show that heterogeneous networks yield the most effective rumor and anti-rumor spreading. Besides, the sooner authority releases anti-rumor and the more attractive anti-rumor is, the less rumor influence is. What’s more, these findings suggest that individuals’ ability to control themselves and identify rumor accurately should be improved to reduce negative impact of rumor effectively. The results are helpful to understand better the mechanism of rumor propagation and refutation in OSNs.

Rumor Propagation Model for Complex Network with Non-Uniform Propagation Rates

2014 ◽  
Vol 596 ◽  
pp. 868-872 ◽  
Author(s):  
Rui Sun ◽  
Wan Bo Luo
Keyword(s):  
Mean Field Theory ◽  
Mean Field ◽  
Propagation Rate ◽  
Propagation Model ◽  
Scale Free Network ◽  
Propagation Characteristics ◽  
Affecting Factors ◽  
Scale Free ◽  
Rumor Propagation ◽  
Free Network

Considering propagation characteristics and affecting factors of rumor in real-world complex networks, this paper described different propagation rates of different nodes by introducing the rumor acceptability function. Based on mean-field theory, this paper presented a rumor propagation model with non-uniform propagation rate, and then simulated the behaviour of rumor propagation on scale-free network and calculated the propagation thresholds by corresponding dynamics equation. Theoretical analysis and simulation results show that nodes with different rumor acceptability could lead to slowing the spread of rumors, make positive propagation threshold arise, and effectively contain the outbreak and reduce the risk of rumors.

Precipitation in small systems—II. Mean field equations more effective than population balance

1996 ◽  
Vol 51 (19) ◽  
pp. 4423-4436 ◽  
Author(s):  
S. Manjunath ◽  
K.S. Gandhi ◽  
R. Kumar ◽  
Doraiswami Ramkrishna
Keyword(s):  
Mean Field ◽  
Population Balance ◽  
Field Equations ◽  
Small Systems ◽  
Mean Field Equations

Solution of the mean field equations for spontaneous fission

1987 ◽  
Vol 35 (3) ◽  
pp. 1007-1027 ◽  
Author(s):  
G. Puddu ◽  
J. W. Negele
Keyword(s):  
Spontaneous Fission ◽  
Mean Field ◽  
Field Equations ◽  
Mean Field Equations ◽  
The Mean

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.

Mean field equations with probability measure in 2D-turbulence

2014 ◽  
Vol 63 (S1) ◽  
pp. 255-264 ◽  
Author(s):  
Tonia Ricciardi ◽  
Gabriella Zecca
Keyword(s):  
Probability Measure ◽  
Mean Field ◽  
Field Equations ◽  
2D Turbulence ◽  
Mean Field Equations
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