Global dynamics analysis and control of a rumor spreading model in online social networks

2019 ◽  
Vol 526 ◽  
pp. 120903 ◽  
Author(s):  
Linhe Zhu ◽  
Xiao Zhou ◽  
Yimin Li
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Global Dynamics ◽  
Dynamics Analysis ◽  
Rumor Spreading ◽  
Spreading Model ◽  
And Control

The influence of positive news on rumor spreading in social networks with scale-free characteristics

2018 ◽  
Vol 29 (09) ◽  
pp. 1850078 ◽  
Author(s):  
Yongcong Luo ◽  
Jing Ma
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Transition Probability ◽  
Probability Method ◽  
Spreading Process ◽  
Rumor Spreading ◽  
Scale Free ◽  
Spreading Model ◽  
Text Model ◽  
The Impact

We explore the impact of positive news on rumor spreading in this paper. It is a fact that most of the rumors related to hot events or emergencies can be propagated rapidly on the hotbed of online social networks. In Chinese words, it is better to divert rather than block. Therefore, we propose the spreading model [Formula: see text] in which positive news is a good factor to guide rumor spreading. Based on transition probability method, we have got the spreading parameters of the [Formula: see text] model by running the rumor spreading process in online social networks with scale-free characteristics. The results give a good proof that improving the activity of the positive news spreader [Formula: see text] derived from the [Formula: see text] model can guide and restrain the spreading speed of rumor smoothly.

scholarly journals Subgraphs of Interest Social Networks for Diffusion Dynamics Prediction

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 492
Author(s):  
Valentina Y. Guleva ◽  
Polina O. Andreeva ◽  
Danila A. Vaganov
Keyword(s):  
Social Networks ◽  
Sampling Method ◽  
Building Blocks ◽  
Global Dynamics ◽  
Diffusion Dynamics ◽  
Different Types ◽  
Prediction And Control ◽  
Path Lengths ◽  
And Control ◽  
Diffusion Prediction

Finding the building blocks of real-world networks contributes to the understanding of their formation process and related dynamical processes, which is related to prediction and control tasks. We explore different types of social networks, demonstrating high structural variability, and aim to extract and see their minimal building blocks, which are able to reproduce supergraph structural and dynamical properties, so as to be appropriate for diffusion prediction for the whole graph on the base of its small subgraph. For this purpose, we determine topological and functional formal criteria and explore sampling techniques. Using the method that provides the best correspondence to both criteria, we explore the building blocks of interest networks. The best sampling method allows one to extract subgraphs of optimal 30 nodes, which reproduce path lengths, clustering, and degree particularities of an initial graph. The extracted subgraphs are different for the considered interest networks, and provide interesting material for the global dynamics exploration on the mesoscale base.

Susceptible-Infectious-Critical-Recovered rumor spreading model in social networks

2021 ◽  
Author(s):  
Wang Hongmei ◽  
Qiu Liqing ◽  
Tan Kun ◽  
Cui Junwei
Keyword(s):  
Social Networks ◽  
Theoretical Analysis ◽  
Critical State ◽  
Effective Measure ◽  
Rumor Spreading ◽  
Spreading Model ◽  
Rumor Propagation ◽  
Number Formula ◽  
Simulation Results ◽  
Next Generation Matrix

As an important area of social networks, rumor spread has attracted the attention of many scholars. It aims to explore the rumor propagation, and to propose effective measures to curb the further spread of rumors. Different from some existing works, this paper believes that susceptible persons affected by rumor-refuting information will first enter the critical state, while ones who related to rumors will directly turn into the spread state. Therefore, this paper proposes a Susceptible-Infectious-Critical-Recovered (SICR) rumor model. In addition, considering that infectious persons with high levels of refuting rumors may cause emotional resonance among individuals, this model adds a connecting edge from the recovered to the infectious who are triggered by the information of refuting the rumors. First, the basic regeneration number [Formula: see text] is obtained by using the next generation matrix method. Then, the global stability of the rumor-free equilibrium [Formula: see text] and the persistence of rumor propagation are proved in detail in theoretical analysis. The simulation results show that the existence of a critical state can reduce the influence of rumors. Rumor refutation mechanism, as soon as possible to curb the spread of rumors, is an effective measure.

scholarly journals Modeling and Analysis of Rumor Spreading with Social Reinforcement Mechanism

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Yuan Xu ◽  
Renjie Mei ◽  
Yujie Yang ◽  
Zhengmin Kong
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Diffusion Mechanism ◽  
Practical Significance ◽  
Propagation Mechanism ◽  
Spreading Process ◽  
Rumor Spreading ◽  
Modeling And Analysis ◽  
Reinforcement Mechanism ◽  
Theoretical Results

It is of great practical significance to figure out the propagation mechanism and outbreak condition of rumor spreading on online social networks. In our paper, we propose a multi-state reinforcement diffusion model for rumor spreading, in which the reinforcement mechanism is introduced to depict individual willingness towards rumor spreading. Multiple intermediate states are introduced to characterize the process that an individual's diffusion willingness is enhanced step by step. We study the rumor spreading process with the proposed reinforcement diffusion mechanism on two typical networks. The outbreak thresholds of rumor spreading on both two networks are obtained. Numerical simulations and Monte Carlo simulations are conducted to illustrate the spreading process and verify the correctness of theoretical results. We believe that our work will shed some light on understanding how human sociality affects the rumor spreading on online social networks.

Rumor spreading model considering hesitating mechanism in complex social networks

2015 ◽  
Vol 437 ◽  
pp. 295-303 ◽  
Author(s):  
Ling-Ling Xia ◽  
Guo-Ping Jiang ◽  
Bo Song ◽  
Yu-Rong Song
Keyword(s):  
Social Networks ◽  
Rumor Spreading ◽  
Spreading Model
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