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.

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.

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.

Dynamical behaviors and spatial diffusion in a psychologically realistic rumor spreading model

2020 ◽  
Vol 31 (02) ◽  
pp. 2050034
Author(s):  
Yingying Cheng ◽  
Liang’an Huo ◽  
Liang Ma ◽  
Hongyuan Guo
Keyword(s):  
Psychological Factors ◽  
Cumulative Effect ◽  
Threshold Condition ◽  
Field Equations ◽  
Final Size ◽  
Dynamical Mechanism ◽  
Rumor Spreading ◽  
Spreading Model ◽  
Mean Field Equations ◽  
Sensory Intensity

The spread of rumors has caused serious social and economic problems, especially during emergencies. Reducing the harm caused by rumors requires understanding the dynamical mechanism by which they propagate. To include the influence of time-dependent psychological factors, this paper proposes an improved rumor spreading model and derives mean-field equations describing the dynamics of rumor spreading. The psychological factors considered are the attenuation of individual interest, the cumulative effect of memory, and changes in sensory intensity with time. We also obtain the threshold condition of rumor spreading. Numerical simulations are used to verify our theoretical results. It is proved that the extremum of the cumulative effect of memory and the rumor attraction rate are positively correlated with the peak number of rumor spreaders, and negatively with the time required to reach the final rumor size. Time grows geometrically, while sensory intensity grows arithmetically. The initial approval rate of the memory accumulation effect and the stifling mechanism have little effect on the final rumor size. Finally, it is found that increasing the attenuation of interest coefficient reduces the time needed for the rumor to reach its final size.

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.

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