一种基于PageRank的微博用户影响度评估算法  

A PageRank-based Algorithm to Estimate Microblog Users' Influences

作　　者：欧卫 欧缤忆 谢赞福[1] 肖政宏[1] 彭平[1] 

机构地区：[1]广东技术师范学院计算机学院,广东广州510665 [2]江西师范大学心理学院,江西南昌330027

出　　处：《计算机与现代化》2013年第12期34-37,60,共5页Computer and Modernization

摘　　要：微博已成为主流的在线社交网络平台,用户的影响力已成为衡量用户价值的一个重要指标。本文基于PageRank算法,通过分析用户之间的兴趣相似度、相对发帖活跃度、相互反馈互动程度来计算一个用户对其所关注的用户的关注程度,提出一个能够评估用户在微博上实际影响度WeiboRank算法。实验数据分析表明,该算法得到的用户影响度值能较客观地反映用户在其所处的虚拟社交网络中的实际影响度。By analogizing microblog users to nodes and the followingship of a user to others to directed edges in a network graph , PageRank algorithm can be used to compute the influence of a microblog user .However the unrevised PageRank is based on the condition that the weights of directed edges of a node pointing to others are equal .Obviously this condition is not applicable to compute the influence of microblog users .Because of the existence of natural differences among interests , ideologies , posting fre-quencies of users , someone must follow different users she or he following to different extend .By computing the interest similari-ty, relative posting frequency , feedback frequency of a user to another to measure the following degrees of the user to her or his followings , this article develops a new algorithm , WeiboRank , which is based on PageRank to compute the influence of a user on a microblog platform.The experiment result shows that the influence value of a user computed by using WeiboRank can reflect the actual influence of the user in an on-line social circle in which she or he is .

关 键 词：PAGERANK算法 社交网络 影响度评估 相似度 用户兴趣 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]