Modeling complex social contagions in big data era
In big data era,individuals are surrounded by various kinds of social medium,such as Facebook,Twitter and Microblog.These social media produce vast information every day and support diverse social contagions.However,the dynamics and mechanisms of these social contagions are still obscure and unrevealed because of the big data.In this paper,we propose a novel non-Markovian social contagion model to study behavior spreading under the environment of big data,in which a fraction of global individuals can transmit the behavior information to every susceptible individual,and the remaining local individuals can only transmit the behavior information to neighbors.Through extensive numerical simulations,we find that the global individuals markedly promote the behavior spreading and decrease the critical information transmission probability.In addition,we note that the degree heterogeneity of social network does not change the phenomena qualitatively.Our results may shed some lights in predicting and controlling social contagions.In further,the proposed model may be applied in real simulation platforms for emergency management in big data era.
complex networks social contagions behavior spreading simulation model
Xuyang Ding Zhangjian Wu Wantao Chen Ying Liu Ying Xie Shiming Cai
Power China Chengdu Engineering Corporation Limited,Chengdu 610072,P.R.China Power Construction Corporation of China,Beijing 100048,P.R.China Southwest University for Nationalities,Chengdu 610041,P.R.China Big Data Research Center,University of Electronic Science and Technology of China,Chengdu 611731,P.R
国际会议
重庆
英文
830-834
2017-03-25（万方平台首次上网日期，不代表论文的发表时间）