计算机工程与科学2017，Vol.39Issue(3)：477-484,8.DOI:10.3969/j.issn.1007-130X.2017.03.011
社交网络用户影响力分析ABP算法研究与应用
An ABP algorithm for user influence analysis in social networks
摘要
Abstract
As a means of communication,social networks have taken root in people's hearts.The user data of social networks has a lot of value in this big data era.With the opening of Twitter Application Programming Interface (API),Twitter,as a social networking site,has become a popular research object,especially the user influence.The PageRank algorithm has long been in use to calculate users' influence,however,it is too dependent on the following relationship between users,so the ranking of users does not have strong timeliness.We introduce user activity to improve the PageRank algorithm,which has a certain degree of timeliness,but not convincing and accurate.We propose a new algorithm called PageRank activity based (ABP) algorithm according to the time distribution of user activity,and corresponding ageing weight factors are applied to the active degree of different periods of time.Finally we taking Twitter as the research object and combining with the social relationship graph,we prove that the ABP algorithm is more efficient and persuasive through an example analysis,and it can be more accurate in improving the ranking of active users and reducing the ranking of inactive users.关键词
社交网络/数据获取/用户影响力/ABP算法Key words
social network/data acquisition/user influence/ABP algorithm分类
信息技术与安全科学引用本文复制引用
张晓双,夏群峰,刘渊,徐雁飞..社交网络用户影响力分析ABP算法研究与应用[J].计算机工程与科学,2017,39(3):477-484,8.基金项目
江苏省自然科学基金(BK20151131) （BK20151131）
中央高校基本科研业务费专项资金(JUSRP51614A) （JUSRP51614A）
