计算机科学 ›› 2013, Vol. 40 ›› Issue (Z11): 26-28.

• 无线网络与通信 • 上一篇    下一篇

时序阵发性对信息传播的影响

邓冬梅,朱建,陈端兵,高辉   

  1. 电子科技大学计算机科学与工程学院 成都611731;电子科技大学计算机科学与工程学院 成都611731;电子科技大学计算机科学与工程学院 成都611731;电子科技大学计算机科学与工程学院 成都611731
  • 出版日期:2018-11-16 发布日期:2018-11-16

Influence of Bursty on Information Diffusion

DENG Dong-mei,ZHU Jian,CHEN Duan-bing and GAO Hui   

  • Online:2018-11-16 Published:2018-11-16

摘要: 近年来,传播动力学是网络研究的一个热门话题,传统的信息传播都是在静态网络上进行研究的,但现实生活中许多网络是有时序的。到目前为止,已有很多学者针对时序阵发性对信息传播影响做了研究,结果表明对不同的数据集、不同的节点感染方式,阵发性对信息传播呈现的作用是不同的。针对此现象,通过构建DCW空模型消除原数据的阵发性特征,分析信息在原数据和空模型数据上的传播情况,以找到阵发性对传播呈现不同影响的原因。

关键词: 时序网络,传播,阵发性,空模型

Abstract: In recent years,the transmission dynamics is a hot topic in network research,traditional information dissemination researches are based on static network,but many actual networks are temporal.So far,many scholars have researched the impact of bursty on information dissemination,and the results show that bursty presents different roles for information dissemination on different data sets and different nodes infection way.Regarding to this phenomenon,stu-dying the influence of bursty on information dissemination by using DCW null model,and analyzes information spreading on the original data and the null model data,and to find out the reason why bursty shows different effects on the spreading.

Key words: Temporal network,Propagation,Bursty,Null model

[1] 周涛,傅忠谦,等.复杂网络上传播动力学研究综述[J].电子科技大学,中国:自然科学进展,2005,5(5):513-518
[2] 丁军平,蔡皖东.面向P2P特定信息的传播动力学模型研究[J].中国:计算机科学,2011,38(11)
[3] Petter H,Jari S.Temporal networks[J].Phys.Rep,2012,519:97-125
[4] Alexei V,Joao G,Zoltan D,et al.Modeling bursts and heavytails in human dynamics[J].Phys.Rev.E 73,036127,2006
[5] 陈琳,刘维奇.重尾分布族及其关系图[J].高校应用数学学报,2009,24(2):166-174
[6] 樊超,郭进利,韩筱璞.人类行为动力学研究综述[J].复杂系统与复杂性科学,2011,1(17):1672-3813
[7] Alexsandro M C,Sebastian G.Epidemics scenarios in the “Romantic network”[J].PLoS ONE,2012,7(11):e49009
[8] Duygu B,Vittoria C,Bruno G,et al.Multiscale mobility net-works and the large scale spreading of infectious diseases[J].PNAS,2009,106(51):21484-21489
[9] Manuel G,Bernahard S.Influence maximization in continuoustime diffusion networks[J].ICML,2012,5-1682:10750658
[10] Jiang Z Q,Xie W J,Li M X,et al.Calling patterns in human communication dynamics[J].PNAS:2013,110(5):1600-1605
[11] Adrien G,Hakim H,Cecile F.Predicting the temporal dynamics of information diffusion in social networks[J].arXiv:1302.5235v2[cs.SI],2013
[12] Petter H.Eepidemiologically optimal static networks from temporal network data[J].arXiv:1302[physics.soc-ph],2013
[13] Karsai M,Kivela M,Pan R K,et al.Small but slow world:how network topology and burstiness slow down spreading[J].Phys.Rev.E 83,025102(R),2011
[14] Alexei V,Balazs R,Ras L,et al.Impact of non-Poisson activity patterns on spreading processes[J].Phys.Rev.Lett.98,158702,2007
[15] 郭进利,汪丽娜.幂律指数在1与3之间的一类无标度网络[J].中国:物理学报,2007,56(10):5635-05
[16] Taro T,Naoki M,Petter H.Bursty communication patterns facilitate spreading in a threshold-based epidemic dynamics[J].nlin.physics.soc-ph,2012
[17] Crocha L E,Liljeros F,HOlME P.Simulated epidemics in an empirical spatiotemporal network of 50,5sexual contacts[J].PLoSComput.Biol.7,e1001109,2011
[18] Karimi F,Holme P,unpublished,2012
[19] Lorenzo I,Ciro C,Wouter V.What’s in a crowd?Analysis offace-to-face behavioral networks[J].J.Theor.Biol.,2011(271):166-180
[20] Seth M,Chen Guang-zhu,Jure L.Information diffusion and external influence in networks[J].Stanford University:ACM,2012:33-41

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!