ISRT rumor spreading model with different influence mechanisms in social networks

被引:0
作者
Wang, Hongmei [1 ]
Qiu Liqing [1 ]
Sun, Chengai [1 ]
机构
[1] Shandong Univ Sci & Technol, Wisdom Mine Indormat Technol Coll Comp Sci & Engn, Shandong Prov Key Lab, Qingdao 266590, Shandong, Peoples R China
来源
INTERNATIONAL JOURNAL OF MODERN PHYSICS C | 2023年 / 34卷 / 01期
基金
中国国家自然科学基金;
关键词
Rumor spreading; kinetic equations; steady state; PROPAGATION;
D O I
10.1142/S0129183123500031
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Rumor, as an important form of information dissemination, has always been a research hotspot in the field of complex networks. How to better understand the rules of rumor propagation and establish a practical dissemination model is a significant challenge. To further study the state transfer in information transmission, this paper established the Ignorant-Spreader-Stifler-Transition (ISRT) model, introduced different influence mechanisms and calculate the influence rate accurately by function. Specifically, (1) Based on SIR model, this paper introduces the transition state, considering that transition may awaken spontaneously to spread rumors due to individual cognition. In this paper, the ratio of the current communicator and the degree of doubt of the transition are introduced into the spontaneous arousal function. (2) This paper redefines the propagation probability function and the forgetting probability function, and introduces the time function to describe the rate from the propagator to the restorer. (3) Due to the presence of highly emotional leader propagators in the network who would awaken the immune to spread rumors again, the model added a link from the recovering person to the infected person. Finally, the nonpropagation equilibrium point E-0 and propagation equilibrium point E-1 are obtained by establishing the mean field equation. The experimental results show that different influencing mechanisms can more accurately locate the stage change of rumor transmission, which provides theoretical support for more effective control of information transmission.
引用
收藏
页数:18
相关论文
共 19 条
[1]   EPIDEMICS + RUMOURS [J].
DALEY, DJ ;
KENDALL, DG .
NATURE, 1964, 204 (496) :1118-&
[2]   The mathematics of infectious diseases [J].
Hethcote, HW .
SIAM REVIEW, 2000, 42 (04) :599-653
[3]   The Simple Rules of Social Contagion [J].
Hodas, Nathan O. ;
Lerman, Kristina .
SCIENTIFIC REPORTS, 2014, 4
[4]  
Jain A., 2016, SOC NETW ANAL MIN, V6, P1
[5]   Contribution to the mathematical theory of epidemics [J].
Kermack, WO ;
McKendrick, AG .
PROCEEDINGS OF THE ROYAL SOCIETY OF LONDON SERIES A-CONTAINING PAPERS OF A MATHEMATICAL AND PHYSICAL CHARACTER, 1927, 115 (772) :700-721
[6]  
Moreno Y, 2004, PHYS REV E, V69, DOI 10.1103/PhysRevE.69.066130
[7]   The independent spreaders involved SIR Rumor model in complex networks [J].
Qian, Zhen ;
Tang, Shaoting ;
Zhang, Xiao ;
Zheng, Zhiming .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2015, 429 :95-102
[8]   Effect of individual behavior on epidemic spreading in activity-driven networks [J].
Rizzo, Alessandro ;
Frasca, Mattia ;
Porfiri, Maurizio .
PHYSICAL REVIEW E, 2014, 90 (04)
[9]   The impact of group propagation on rumor spreading in mobile social networks [J].
Sahafizadeh, Ebrahim ;
Ladani, Behrouz Tork .
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2018, 506 :412-423
[10]  
Wang C, 2014, CHINA COMMUN, V11, P24, DOI 10.1109/CC.2014.7004521