A SEIR-based Model for Virus Propagation on SNS

Chao Wang, Ke Xu, Gaoyu Zhang

Abstract: In this paper, we propose a general stochastic model for virus propagation on the online social network. The model considers the time interval of users re-login in SNS network, the number of users in one's friend list, and propagation mechanism, utilizes SEIR model, which is an epidemic model, and finally establishes the dynamic evolution equations. The dynamic evolution equations describe the change of susceptible, exposed, infectious and recovered nodes' quantities as time grows respectively, and reflect the influences of all these factors on virus propagation. Simulation results show that virus spreads faster and has a larger scale while users login in their SNS accounts more frequently. The greater the number of friends in users' friend lists, the shorter the spread duration is and the lager the scale of virus propagation reaches. Besides, these consequences show that the proposed model, having the same characteristics with SNS, has advantages to describe virus propagation on SNS.

External IDs:dblp:conf/eidwt/WangXZ13