基于R-C模型的微博社区用户影响力分析

摘要

微博社区中用户的影响力对微博信息的有效传播具有重要意义.为了快速并准确地寻找微博社区信息传播的规律,提出一种基于微博社区计算用户影响力的USR算法.首先提取种子用户的数据,利用R-C模型进行微博社区发现,在划分好的社区中选取一个社区;然后依据USR算法,对社区内的用户进行影响力计算;最后输出用户的影响力.以新浪微博数据集为例,提出孤立点的概念和信息传播实际影响人次覆盖率评价指标,将USR算法与传统影响力算法进行对比.实验结果表明,使用USR算法能够得到较优的结果.%The microblog community users' influence has great significance in effective dissemination of microblog information.To rapidly and accurately find the regularity of micro-blog community's information dissemination,a microblog community users' importance algorithm was presented.Firstly,seed user data are extracted and microblog communities are detected by using R-C model,and one community form the divided communities is selected.Then,the influence of user in the community is calculated according to USR algorithm.Finally,the influence of user in the community is outputted.Taking the sina microblog data sets as example,the concept of isolated point and the coverage evaluation index of information dissemination impact person-time were proposed.We computed the users' influence by comparing USR algorithm with other traditional algorithms.Experiments show that the USR algorithm can acquire better result than other algorithms.