基于概率加权通信社区SIR模型及信息扩散预测方法研究  

Probability-Weighted Communication Community SIR Model and Prediction Method Based on Information Diffusion

作　　者：卫红权[1] 陈鸿昶[1] 刘力雄[1] 兰巨龙[1] 

机构地区：[1]国家数字交换系统工程技术研究中心,河南郑州450002

出　　处：《信息工程大学学报》2014年第6期678-685,共8页Journal of Information Engineering University

基　　金：国家自然科学基金资助项目(61171108);国家973计划资助项目(2012CB315901;2012CB315905)

摘　　要：针对当前电信网如何有效刻画敏感信息传播特性及对信息扩散进行预测的难题,提出了基于概率加权通信社区信息传播模型及扩散范围预测方法,该模型基于复杂网络传播动力学,考虑了电信网通信社区中用户之间的关系紧密程度、不同的用户类型以及社区中结构等因素对于信息传播的影响。采用该模型并通过扩散过程推演方法进行仿真,仿真结果中可以准确得到各类个体随时间演化的变化趋势。This paper proposes a probabilistic model of information dissemination and diffusion weighted prediction method to effectively portray the propagation characteristics of sensitive informa- tion and to effectively predict the diffusion of information on the problem. The method is based on the scope of the model and on the transmission dynamics of complex networks, taking into account the telecommunications Netcom letter community closeness between users of different types of users and the community structure and other factors affecting the dissemination of information. Using this model and simulation results, the evolution trends over time can be accurately obtained of various types of self-diffusion process through inference methods.

关 键 词：复杂网络 电信网 传播动力学 信息传播 信息扩散 

分 类 号：TN915[电子电信—通信与信息系统]