Rumor Spreading Model with Trust Mechanism in Complex Social Networks

In this paper, to study rumor spreading, we propose a novel susceptible-infected-removed （SIR） model by introducing the trust mechanism. We derive mean-field equations that describe the dynamics of the SIR model on homogeneous networks and inhomogeneous networks. Then a steady-state analysis is cond...

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Published inCommunications in theoretical physics Vol. 59; no. 4; pp. 510 - 516
Main Author 王亚奇 杨晓元 韩益亮 王绪安
Format Journal Article
LanguageEnglish
Published 01.04.2013
Subjects
Computer simulation
Mathematical analysis
Mathematical models
Networks
SIR模型
Social networks
Spreading
Terminals
Thresholds
临界阈值
传播模型
信任机制
动态描述
平均场方程
社会网络
谣言
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Summary:In this paper, to study rumor spreading, we propose a novel susceptible-infected-removed （SIR） model by introducing the trust mechanism. We derive mean-field equations that describe the dynamics of the SIR model on homogeneous networks and inhomogeneous networks. Then a steady-state analysis is conducted to investigate the critical threshold and the finaJ size of the rumor spreading. We show that the introduction of trust mechanism reduces the final rumor size and the velocity of rumor spreading, but increases the critical thresholds on both networks. Moreover, the trust mechanism not only greatly reduces the maximum rumor influence, but also postpones the rumor terminal time, which provides us with more time to take measures to control the rumor spreading. The theoretical results are confirmed by sufficient numerical simulations.
Bibliography:WANG Ya-Qi, YANG Xiao-Yuan , HAN Yi-Liang , and WANG Xu-An
rumor spreading, SIR model, homogeneous network, inhomogeneous network
11-2592/O3
In this paper, to study rumor spreading, we propose a novel susceptible-infected-removed （SIR） model by introducing the trust mechanism. We derive mean-field equations that describe the dynamics of the SIR model on homogeneous networks and inhomogeneous networks. Then a steady-state analysis is conducted to investigate the critical threshold and the finaJ size of the rumor spreading. We show that the introduction of trust mechanism reduces the final rumor size and the velocity of rumor spreading, but increases the critical thresholds on both networks. Moreover, the trust mechanism not only greatly reduces the maximum rumor influence, but also postpones the rumor terminal time, which provides us with more time to take measures to control the rumor spreading. The theoretical results are confirmed by sufficient numerical simulations.
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0253-6102
DOI:10.1088/0253-6102/59/4/21