SICR rumor spreading model in complex networks: Counterattack and self-resistance

2014 ◽  
Vol 405 ◽  
pp. 159-170 ◽  
Author(s):  
Yongli Zan ◽  
Jianliang Wu ◽  
Ping Li ◽  
Qinglin Yu
Keyword(s):  
Complex Networks ◽  
Rumor Spreading ◽  
Spreading Model

scholarly journals Steady-State Analysis of SECIR Rumor Spreading Model in Complex Networks

2019 ◽  
Vol 10 (03) ◽  
pp. 75-86
Author(s):  
Yujiang Liu ◽  
Chunmei Zeng ◽  
Youquan Luo
Keyword(s):  
Steady State ◽  
Complex Networks ◽  
Rumor Spreading ◽  
Steady State Analysis ◽  
Spreading Model ◽  
State Analysis

How the node’s vital and tie strength effect rumor spreading on social network

2019 ◽  
Vol 30 (06) ◽  
pp. 1950046
Author(s):  
Liang’an Huo ◽  
Tingting Lin ◽  
Chen Liu ◽  
Xing Fang
Keyword(s):  
Social Network ◽  
Complex Networks ◽  
Numerical Solutions ◽  
Spreading Rate ◽  
Tuning Parameter ◽  
Tie Strength ◽  
Time Step ◽  
Rumor Spreading ◽  
Spreading Model ◽  
Positive Quantity

The spread of rumors on complex networks has attracted wide attention in the field of management. In this paper, the generalized rumor spreading model is modified to take into account the vital of the spreader and the tie strength for the pairwise contacts between nodes in complex networks at degree-dependent spreading rate. Concretely, we introduce the infectivity exponent [Formula: see text], and the degree influenced real exponent [Formula: see text] into the analytical rumor spreading model. Rumor infectivity, [Formula: see text], where [Formula: see text], defines that each spreader node may contact [Formula: see text] neighbors within one time step. The tie strength between two nodes with degrees [Formula: see text] and [Formula: see text] are measured by [Formula: see text], [Formula: see text] is the degree influenced real exponent which depends on the type of complex networks and [Formula: see text] is a positive quantity. We use a tuning parameter [Formula: see text] to combine both the effect of the vital nodes and the strength of connectivity between nodes. We use analytical and numerical solutions to examine the threshold behavior and dynamics of the model on several models of social network. It was found that the infectivity exponent [Formula: see text], the degree influenced real exponent [Formula: see text] and tuning parameter [Formula: see text] affect the rumor threshold, one can adjust the parameters to control the rumor threshold which is absent for the standard rumor spreading model.

Dynamical analysis of rumor spreading model in multi-lingual environment and heterogeneous complex networks

2020 ◽  
Vol 536 ◽  
pp. 391-408 ◽  
Author(s):  
Jiarong Li ◽  
Haijun Jiang ◽  
Xuehui Mei ◽  
Cheng Hu ◽  
Guoliang Zhang
Keyword(s):  
Complex Networks ◽  
Dynamical Analysis ◽  
Rumor Spreading ◽  
Spreading Model

Dynamical analysis of rumor spreading model in homogeneous complex networks

2019 ◽  
Vol 359 ◽  
pp. 374-385 ◽  
Author(s):  
Jiarong Li ◽  
Haijun Jiang ◽  
Zhiyong Yu ◽  
Cheng Hu
Keyword(s):  
Complex Networks ◽  
Dynamical Analysis ◽  
Rumor Spreading ◽  
Spreading Model ◽  
Homogeneous Complex

SIRaRu rumor spreading model in complex networks

2014 ◽  
Vol 398 ◽  
pp. 43-55 ◽  
Author(s):  
Jiajia Wang ◽  
Laijun Zhao ◽  
Rongbing Huang
Keyword(s):  
Complex Networks ◽  
Rumor Spreading ◽  
Spreading Model

scholarly journals Dynamics of the rumor-spreading model with hesitation mechanism in heterogenous networks and bilingual environment

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Shuai Yang ◽  
Haijun Jiang ◽  
Cheng Hu ◽  
Juan Yu ◽  
Jiarong Li
Keyword(s):  
Lyapunov Method ◽  
Reproduction Number ◽  
Model Parameters ◽  
Rumor Spreading ◽  
Spreading Model ◽  
Reductio Ad Absurdum ◽  
The Stability ◽  
The Impact ◽  
Theoretical Results ◽  
The Basic Reproduction Number

Abstract In this paper, a novel rumor-spreading model is proposed under bilingual environment and heterogenous networks, which considers that exposures may be converted to spreaders or stiflers at a set rate. Firstly, the nonnegativity and boundedness of the solution for rumor-spreading model are proved by reductio ad absurdum. Secondly, both the basic reproduction number and the stability of the rumor-free equilibrium are systematically discussed. Whereafter, the global stability of rumor-prevailing equilibrium is explored by utilizing Lyapunov method and LaSalle’s invariance principle. Finally, the sensitivity analysis and the numerical simulation are respectively presented to analyze the impact of model parameters and illustrate the validity of theoretical results.

scholarly journals Dynamical analysis of a stochastic rumor-spreading model with Holling II functional response function and time delay

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Liang’an Huo ◽  
Xiaomin Chen
Keyword(s):  
Time Delay ◽  
White Noise ◽  
Functional Response ◽  
Response Function ◽  
Rapid Development ◽  
Dynamical Behavior ◽  
Deterministic System ◽  
Rumor Spreading ◽  
Spreading Model ◽  
Holling Ii Functional Response

AbstractWith the rapid development of information society, rumor plays an increasingly crucial part in social communication, and its spreading has a significant impact on human life. In this paper, a stochastic rumor-spreading model with Holling II functional response function considering the existence of time delay and the disturbance of white noise is proposed. Firstly, the existence of a unique global positive solution of the model is studied. Then the asymptotic behavior of the global solution around the rumor-free and rumor-local equilibrium nodes of the deterministic system is discussed. Finally, through some numerical results, the validity and availability of theoretical analysis is verified powerfully, and it shows that some factors such as the transmission rate, the intensity of white noise, and the time delay have significant relationship with the dynamical behavior of rumor spreading.

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