广东工业大学学报 ›› 2016, Vol. 33 ›› Issue (03): 49-54.doi: 10.3969/j.issn.1007-7162.2016.03.009

• 综合研究 • 上一篇    下一篇

基于PageRank的微博用户影响力度量

王晓彤   

  1. 广东工业大学 计算机学院,广东 广州 510006
  • 收稿日期:2015-03-03 出版日期:2016-05-19 发布日期:2016-05-19
  • 作者简介:王晓彤(1989-),男,硕士研究生,主要研究领域为社交网络中的用户影响力.
  • 基金资助:

    国家自然科学基金资助项目(61100148;61202269)

An Evaluation of Microblog Users’ Influence Based on PageRank

Wang Xiao-tong   

  1. School of Computers, Guangdong University of Technology, Guangzhou 510006, China
  • Received:2015-03-03 Online:2016-05-19 Published:2016-05-19

摘要:

在微博社区中具有较高影响力的用户对信息推荐、市场营销、舆情控制等方面都起着重要作用.针对现有仅考虑网络拓扑结构的影响力研究方法,以微博用户为基础,提出了一种新的微博用户影响力度量模型——UIRank模型.此模型以用户之间的交互行为作为切入点,根据用户不同行为的权重差异确定用户间UIRank值的分配比例.实验证明,文中提出的影响力度量方法相比已有的方法更加准确和高效.

关键词: 社交网络; 用户行为交互; 网络拓扑; 用户影响力; 影响力算法

Abstract:

High-impact users of microblog play an significant role in information recommendation, marketing, public opinion analysis and other areas. Aiming at the existing approaches to users’ influence only considering the network topology and taking the users of microblog as the entry point, a new model for calculating users’ influence is proposed-UIRank model. This model gives adequate consideration to the interaction between users and determines the distribution of the value of UIRank according to the weight difference of different user behaviors. It is proved by the results of the experiments that the method for calculating the users’ influence proposed is more accurate and efficient.

Key words: social networks; user interaction behavior; network topology; user influence; influence algorithm

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