通信学报2016，Vol.37Issue(10)：40-47,8.DOI:10.11959/j.issn.1000-436x.2016194
基于亲和传播的动态社会网络影响力扩散模型
Influence diffusion model based on affinity of dynamic social network
摘要
Abstract
Recently, influence maximization model is a hot issue in the field of social network influence, while the tradi-tional independent cascade model is generally based on static network with a fixed value of activation probability. DDIC model, which was a dynamic network influence diffusion model with attenuation factor was proposed. It calculated the activation probability between nodes via affinity propagation, and according with dynamic segmentation of social net-work time slice, calculation of influence on proliferation of next time slice with the current time slice of activation prob-ability performance decay. The experimental results show that the nodes in the DDIC model have more chances to active the neighbor and the average probability of activing of the DDIC model is higher. Further experiments show that influ-ence value via computing with affinity propagation can reflect the process of the spread model more accurately.关键词
动态社会网络/影响力扩散/亲和传播Key words
dynamic social network/influence diffusion/affinity propagation分类
信息技术与安全科学引用本文复制引用
陈云芳,夏涛,张伟,李晋..基于亲和传播的动态社会网络影响力扩散模型[J].通信学报,2016,37(10):40-47,8.基金项目
国家自然科学基金资助项目（No.61272422）；北京市教育委员会人文社会科学研究计划面上基金资助项目（No.SM201411232005） Foundation Items：The National Natural Science Foundation of China (No.61272422), Humanistic and Social Science Research Plan Project of Beijing Municipal Education Commission (No. SM201411232005) （No.61272422）
