计算机应用研究2018，Vol.35Issue(3)：755-759,764,6.DOI:10.3969/j.issn.1001-3695.2018.03.024
基于邻居节点间相互影响和改进概率的社交网络信息传播模型
Information propagation model with improved probability based on influence of neighbors for social network
张永 1和凯1
作者信息
- 1. 兰州理工大学计算机与通信学院,兰州730050
- 折叠
摘要
Abstract
One of current focus of spreading dynamics research analses the propagation of information in the specific network based on the epidemic dynamics model.According to the characteristics of propagation in social network,this paper added a kind of new node named disguising node based on the susceptible-infectious-recovered (SIR) model,and proposed a model named susceptible-disguising-infectious-recovered (SDIR) to describe the propagation better in social network.Considering the mutual influence of neighbor nodes,it defined three propagation probability functions to improve the SDIR model.The results show,by simulating propagation under different conditions,that information cannot cover the whole network,and Twitter performs better than Sina Micro-blog in efficiency of propagating.Also,the initial infection probability has a significant influence in the information propagation.关键词
社交网络/信息传播/SDIR模型Key words
social network/information propagation/SDIR model分类
信息技术与安全科学引用本文复制引用
张永,和凯..基于邻居节点间相互影响和改进概率的社交网络信息传播模型[J].计算机应用研究,2018,35(3):755-759,764,6.
