摘要
通过分析蛛网态微博关系网的特点,指出识别蛛网态微博关系网中有影响力用户的重要意义.重点探讨微博用户自身属性对用户影响力的作用,结合PageRank算法原理,提出一种蛛网态微博关系网中有影响力用户发现方法(Influential User Discovering Algorithm,IUDA),并基于新浪微博的真实用户数据将该方法与另外两种方法进行对比实验.结果显示,结合用户本身影响值的IUDA方法可以更高质量地发现蛛网态微博网中有影响力用户,客观反映用户的影响力.
Through analyzing the characteristics of the cobweb state micro-blog network, the paper points out the importance of identifying the influential user in the cobweb state micro-blog network.It focuses on the effect of the attributes of micro-blog users itself, combines the principle of PageRank algorithm, and then proposes IUDA（ Influential User Discovering Algorithm） in cobweb state micro-blog relationship net-work to find influential users.Finally, experiments are conducted with the real user data from Sina micro-blog based on this method and are compared with two other methods.The results show that the IUDA method combined with the user itself can find influential users in cobweb state micro-blog network more effectively, and can objectively reflect the user′s influence.
出处
《广东工业大学学报》
CAS
2015年第3期61-66,共6页
Journal of Guangdong University of Technology
基金
广东省教育部产学研结合项目(2012B091000058)
广东省专业镇中小微企业服务平台建设项目(2012B040500034)
关键词
有影响力用户
微博
微博关系网
PAGERANK
中心性分析
PageRank
influential users
micro-blog
micro-blog relationships network
PageRank
centrality analysis
