计算机应用与软件2017，Vol.34Issue(5)：28-32,37,6.DOI:10.3969/j.issn.1000-386x.2017.05.005
PageRank模型的改进及微博用户影响力挖掘算法
IMPROVEMENT OF PAGERANK MODEL AND MINING ALGORITHM OF MICROBLOG USER INFLUENCE
摘要
Abstract
With the development of Web technology, microblog has become one of the most popular social platforms.The calculation of user influence in microblog is the focus of related research.Through the improvement of the PageRank model, a new user influences mining algorithm PR4WB (PageRank for Microblog) is proposed to solve the problem that the traditional PageRank algorithm has too much potential error due to the transfer of page authority value.PR4WB algorithm takes into account the user relationship in microblog while using the concept of social network to link its activity, blog quality and credibility to form a dynamic evaluation model.Experiments based on Twitter data show that,PR4WB algorithm can more accurately and objectively reflect the user's actual influence.关键词
用户影响力/社会网络/微博/推特/PageRank算法Key words
User influence/Social network/Microblog/Twitter/PageRank algorithm分类
信息技术与安全科学引用本文复制引用
毛国君,谢松燕,胡殿军..PageRank模型的改进及微博用户影响力挖掘算法[J].计算机应用与软件,2017,34(5):28-32,37,6.基金项目
国家自然科学基金项目(61273293). （61273293）
