Dynamical analysis of a rumor spreading model with self-discrimination and time delay in complex networks

2019 ◽  
Vol 533 ◽  
pp. 121953 ◽  
Author(s):  
Linhe Zhu ◽  
Gui Guan
Keyword(s):  
Time Delay ◽  
Complex Networks ◽  
Dynamical Analysis ◽  
Rumor Spreading ◽  
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

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.

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

scholarly journals Dynamical Analysis of Rumor Spreading Model With Incubation Mechanism and Activity of Nodes

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 152493-152500 ◽  
Author(s):  
Liang'An Huo ◽  
Fan Ding ◽  
Tingting Lin ◽  
Shengwei Yao
Keyword(s):  
Dynamical Analysis ◽  
Rumor Spreading ◽  
Spreading Model

scholarly journals Optimal Control of Rumor Spreading Model with Consideration of Psychological Factors and Time Delay

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Liang’an Huo ◽  
Chenyang Ma
Keyword(s):  
Optimal Control ◽  
Time Delay ◽  
Psychological Factors ◽  
Control Strategies ◽  
Information Age ◽  
Control Cost ◽  
Rumor Spreading ◽  
Spreading Model ◽  
Official Information ◽  
Type Ii Functional Response

Rumors have rapidly increasing influence on the society as well as individual life in the information age. How to control the spread of such rumors effectively has become an urgent problem to be solved. In this paper, we consider an optimal control of rumor spreading model with psychological factors and time delay. Firstly, we introduce a realistic optimal control of rumor spreading model with consideration of Holling-type II functional response and time delay. Secondly, by introducing two control strategies of both promoting scientific knowledge and releasing official information, we formulate an optimal control problem to minimize both the number of ignorant individuals and spreaders and the control cost. Thirdly, we prove the existence and the necessary conditions of optimal control strategies theoretically based on Pontryagin’s maximum principle. Our results indicate that the proposed control strategies are effective in reducing the number of spreaders and ignorant individuals and minimizing control cost.

scholarly journals Dynamical Analysis of Rumor Spreading Model considering Node Activity in Complex Networks

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Liang’an Huo ◽  
Fan Ding ◽  
Chen Liu ◽  
Yingying Cheng
Keyword(s):  
Complex Networks ◽  
Dynamic Models ◽  
Spreading Rate ◽  
Dynamical Analysis ◽  
Field Equations ◽  
Spreading Process ◽  
Rumor Spreading ◽  
Node Activity ◽  
Activity Rate ◽  
Mean Field Equations

The dynamic models are proposed to investigate the influence node activity has on rumor spreading process in both homogeneous and heterogeneous networks. Different from previous studies, we believe that the activity of nodes in complex networks affects the process of rumor spreading. An active node can have contact with all the nodes it directly links to, while an inactive node could only interact with its active neighbors. We explore the joint effort of activity rate, spreading rate and network topology on rumor spreading process by mean-field equations and numerical simulations, which reveals that there exists a critical curve consisting of critical activity rate and spreading rate; meanwhile, activity rate and spreading rate both have influence on the final rumor spreading scale.

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.

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