计算机科学 ›› 2014, Vol. 41 ›› Issue (2): 201-205.

• 网络与信息安全 • 上一篇    下一篇

基于链路预测的微博用户关系分析

傅颖斌,陈羽中   

  1. 福州大学福建省网络计算与智能信息处理重点实验室 福州350108;福州大学福建省网络计算与智能信息处理重点实验室 福州350108
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受福建省自然科学基金(2013J01232),福建省教育厅重点项目(JK2012003),福建省科技创新平台项目(2009J1007)资助

Relationship Analysis of Microblogging User with Link Prediction

FU Ying-bin and CHEN Yu-zhong   

  • Online:2018-11-14 Published:2018-11-14

摘要: 随着以微博为代表的在线社交网站的发展,微博用户之间形成了复杂的社会网络。针对微博社会网络,研究了影响微博用户之间关系形成的各种因素,提出了基于链路预测的微博用户关系分析模型。首先分析了网络结构特征在微博社会网络中的作用,同时针对微博社会网络的特点,引入微博属性特征,构造基于随机森林的链路预测模型,并将模型应用于新浪微博用户数据集,进行微博用户关系的训练预测,通过比较引入微博属性特征前后的预测性能以及特征的重要性分布,分析了各类特征对微博用户关系形成的影响,揭示了除传统的网络结构特征外,微博属性特征对微博用户关系的形成具有重要的影响力。

关键词: 链路预测,社会网络,微博属性,随机森林 中图法分类号TP393文献标识码A

Abstract: With the development of online social networking sites represented by microblog,the microblogging users form some complex social networks.In order to study the factors that affect the formation of relationship among microblogging users,this paper used link prediction to analyze the relationship of micro-blogging users.Firstly,this paper studied how the features of network structure affect the formation of microblogging network.The features of microblogging attribute were also analyzed and introduced to build a link prediction model based on random forest classifier.The link prediction model was tested on a user data set collected from Sina Weibo.By comparing the prediction perfor-mance with and without the introduction of microblogging attribute features and analyzing the importance distribution of features,we found that besides the network structure features,microblogging attribute features have significant effect on the formation of user relationship,and can improve the prediction performance significantly.

Key words: Link prediction,Social network,Microblogging attribute,Random forest

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