摘要
现有的微博社交网络社区挖掘算法大多基于对微博内容的识别,不但涉及用户隐私,还忽略了用户转发行为的重要性,并且对于社区数量和社区中心的判断具有主观性,社区的重叠结构也不易发现。为解决上述问题,提出了一种基于链路结构和转发行为的微博社交网络重叠社区划分方法,综合考虑微博社交网络链路结构和用户转发行为,通过对用户之间转发行为的对比来提高社区划分的质量,实现了自动快速确定社区数量,并设计了中心节点选择算法,客观合理选定社区中心节点。实验证明所提方法能够发现高质量的微博社交网络重叠社区,在理论研究和实际应用方面都有十分重要的意义。
Most of the existing mining algorithms of microblog social network communities were based on the identification of microblog content,which not only involved the user privacy,but also ignored the importance of user forwarding behavior.The judgment of number and the centers of communities was subjective,and overlapping communities were hard to find.In order to solve the above problems,a method was proposed to divide overlapping communities in microblog social networks based on link structure and forwarding behavior.This method could comprehensively considered the link structure of microblog social network and user forwarding behavior.And it could improve the quality of communities by comparing forwarding behavior between users.The number of communities could be determined automatically and quickly,and the center node selection algorithm was designed to find the centers objectively and reasonably.Experiments showed that this method could find high-quality overlapping communities of microblog social network,which was of great significance in theoretical research and practical application.
作者
张中军
于来行
李润川
ZHANG Zhongjun;YU Laihang;LI Runchuan(School of Computer Science and Technology, Zhoukou Normal University, Zhoukou 466001,China;Traceability Technology of Agricultural Products Quality and Safety Engineering Laboratory of Henan Provincial, Zhoukou 466001,China;Collaborative Innovation Center of Internet Medical and Healthcare in Henan, Zhengzhou 450001, China;Institute of Industrial Technology, Zhengzhou University, Zhengzhou 450001, China)
出处
《郑州大学学报(理学版)》
北大核心
2021年第4期69-76,共8页
Journal of Zhengzhou University:Natural Science Edition
基金
国家自然科学基金项目(61902447)
河南省科技厅科技攻关项目(182102310034)。
关键词
微博
社交网络
重叠社区
模块度
链路结构
micro-blog
social network
overlapping community
modularity
link structure