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Epidemic Spreading Model Based on Social Active Degree in Social Networks 被引量:4

Epidemic Spreading Model Based on Social Active Degree in Social Networks
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摘要 In this paper,an improved Susceptible-Infected-Susceptible(SIS) epidemic spreading model is proposed in order to provide a theoretical method to analyze and predict the spreading of diseases.This model is based on the following ideas:in social networks,the contact probability between nodes is decided by their social distances and their active degrees.The contact probability of two indirectly connected nodes is decided by the shortest path between them.Theoretical analysis and simulation experiment were conducted to evaluate the performance of this improved model.Because the proposed model is independent of the network structure,simulation experiments were done in several kinds of networks,namely the ER network,the random regular network,the WS small world network,and the BA scale-free network,in order to study the influences of certain factors have on the epidemic spreading,such as the social contact active degree,the network structure,the average degree,etc.This improved model provides an idea for studying the spreading rule of computer virus,attitudes,fashion styles and public opinions in social networks. In this paper,an improved Susceptible-Infected-Susceptible(SIS) epidemic spreading model is proposed in order to provide a theoretical method to analyze and predict the spreading of diseases.This model is based on the following ideas:in social networks,the contact probability between nodes is decided by their social distances and their active degrees.The contact probability of two indirectly connected nodes is decided by the shortest path between them.Theoretical analysis and simulation experiment were conducted to evaluate the performance of this improved model.Because the proposed model is independent of the network structure,simulation experiments were done in several kinds of networks,namely the ER network,the random regular network,the WS small world network,and the BA scale-free network,in order to study the influences of certain factors have on the epidemic spreading,such as the social contact active degree,the network structure,the average degree,etc.This improved model provides an idea for studying the spreading rule of computer virus,attitudes,fashion styles and public opinions in social networks.
出处 《China Communications》 SCIE CSCD 2015年第12期101-108,共8页 中国通信(英文版)
基金 supported by National Natural Science Foundation of China 61301091 Shaanxi Province Science and Technology Project 2015GY015
关键词 spreading shortest epidemic connected decided indirectly eigenvalue dynamical friends Frobenius 社会网络 流行模式 传染病模型 跃度 疾病传播 连接节点 仿真实验 网络结构
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  • 1Grassly N C, Fraser C. Mathematical models of infectious disease transmission[J]. Nature Re- views Microbiology, 2008, pp. 477-487. 被引量:1
  • 2Siddhartha Banerjee, Aditya Gopalan, Abhik Kumar Das, and Sanjay Shakkottai. Epidemic Spreading With External Agents[J]. IEEE Trans- actions on Information Theory, 2014, pp. 4125- 4139. 被引量:1
  • 3Cheng-yi Xia, Zhen Wang, Joaquin Sanz, San- dro Melonic, Yamir Moreno, Effects of delayed recovery and nonuniform transmission on the spreading of diseases in complex networks[J]. Physica A, 2013, pp. 1577-1585. 被引量:1
  • 4Barabasi A L, Albert R. Emergence of scaling in random networks[J]. Science, 1999, 286(5439): pp. 509-512. 被引量:1
  • 5J. Ripoll, M. Manzano, E. Calle. Spread of epi- demic-like failures in telecommunication net- works[J]. Physica A, 2014, pp.457-469. 被引量:1
  • 6A. Saumell-Mendiola, M. A. Serrano, and M. Boguna, Epidemic spreading on interconnect- ed networks[J]. Physical Review E, 2012, pp. 026106. 被引量:1
  • 7Tatsuro Kawamoto, Naomichi Hatano. Viral spreading of daily information in online social networks[J]. Physica A, 2014, pp. 34-41. 被引量:1
  • 8Kermack W O, Mckendrick A G. A Contribution to the Mathematical Theory of Epidemics[J]. Royal Society of London Proceedings, 1927, 115(772):700-721. 被引量:1
  • 9Brauer F. The Kermack-McKendrick epidemic model revisited.[J]. Mathematical Biosciences, 2005, 198(2):119-131. 被引量:1
  • 10ZHOU Tao,FU Zhongqian,WANG Binghong.Epidemic dynamics on complex networks[J].Progress in Natural Science:Materials International,2006,16(5):452-457. 被引量:36

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  • 1Leskovec J, McGlohon M, Faloutsos C, et al. Patterns of Cascading Behavior in Large Blog Graphs[ C ]//Prceedings of 2007 SIAM International Conference on Data Mining Minneapolis, Minnesota, USA: 551-556. 被引量:1
  • 2Corporation H P. Impulsive Vaccination SEIR Model with Nonlinear Incidence Rate and Time Delay[ J]. Mathematical Problems in Engineering, 2013(2): 292-319. 被引量:1
  • 3Kawachi K. Deterministic Models for Rumor Transmission [ J ]. Nonlinear Analysis Real World Applications, 2008, 9 (5): 1989-2028. 被引量:1
  • 4Nekovee M, Moreno Y, Bianconi G, et al. Theory of Rumour Spreading in Complex Social Networks [ J ]. Physica A Statistical Mechanics & Its Applications, 2008, 374(1) :457-470. 被引量:1
  • 5Gu J, Li W, Cai X. The Effect of the Forget - Remember Mechanism on Spreading[ J]. European Physical Journal B, 2008, 62 (2) : 247-255. 被引量:1
  • 6Zhao L, Qiu X, Wang X, et al. Rumor Spreading Model Considering Forgetting and Remembering Mechanisms in Inhomogeneous Networks [ J ]. Physiea A Statistical Mechanics & Its Applications, 2013, 392 (4) : 987-994. 被引量:1
  • 7Zan Yongli, Wu Jianliang, Li Ping, et al. SICR Rumor Spreading Model in Complex Networks: Counterattack and Self-Resist- ance[ J]. Physica A Statistical Mechanics & Its Applications, 2014, 405:159-170. 被引量:1
  • 8Zhao Laijun, Xie Wanlin, Gao H O, et al. A Rumor Spreading Model with Variable Forgetting Rate [ J ]. Physica A Statistical Mechanics & Its Applications, 2013, 392(23) : 6146-6154. 被引量:1
  • 9Ebbinghaus H. Memory: A Contribution to Experimental Psychology [ J ]. Annals of Neurosciences, 2013, 20 : 1151-1154. 被引量:1
  • 10Valerie Isham, Simon Harden, Maziar Nekovee. Stochastic Epidemics and Rumours on Finite Random Networks [ J ]. Physica A Statistical Mechanics & Its Applications, 2010, 389(3) : 561-576. 被引量:1

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