南京大学学报(自然科学版) ›› 2017, Vol. 53 ›› Issue (2): 378–.

• • 上一篇    

基于多子网复合复杂网络模型的多关系社交网络重要节点发现算法

宾 晟*,孙更新   

  • 出版日期:2017-03-27 发布日期:2017-03-27
  • 作者简介:青岛大学数据科学与软件工程学院,青岛,266071
  • 基金资助:
    ?基金项目:教育部人文社会科学研究青年项目(15YJC86000),青岛市哲学社会科学规划项目(QDSKL150437)
    收稿日期:2016-12-18
    *通讯联系人,E-mail:binsheng@qdu.edu.cn

Important node detection algorithm for multiple relationships online social network based on multi-subnet composited complex network model

Bin Sheng*,Sun Gengxin   

  • Online:2017-03-27 Published:2017-03-27
  • About author:College of Data Science and Software Engineering,Qingdao University,Qingdao,266071,China

摘要: 为提高社交网络中重要节点评估的效率和有效性,根据社交网络中存在多种相互影响的关系的特性,基于复杂网络理论提出了一种适用于多关系社交网络的重要节点发现算法.首先使用多子网复合复杂网络模型建立包含多种关系的复杂网络,然后采用信号传播方法体现网络中多种关系和节点间的相互影响,以及这些影响的传递性,最后利用矩阵迭代方法模拟信号传播过程,定量分析网络中各节点的重要度.该算法综合了社交网络中节点的全局和局部重要性,考虑了各节点重要度的相互影响,在豆瓣网上的实验结果表明,与传统社交网络重要节点发现算法相比,该算法在迭代次数、涵盖率等指标上都有较大改善,有助于提高社交网络中舆情分析、社团结构发现、信息传播等工作的效率和准确性.

Abstract: The purpose of this work is to improve efficiency and accuracy of important node evaluation in online social network.Online social networks is becoming a popular form of social information network.There are frequently many kinds of relationships in an online social network.Considering the characteristics of multiple relationships which would interrelate with each other in online social network,important node detection algorithm for multiple relationships online social network was proposed.Classical complex networks mainly describe the same kind entities and their relationships.However,multi-subnet composited complex network is one model describing different kind entities and their relationships.Firstly,complex network where there are multiple relationships is constructed based on multi-subnet composited complex network model,in which subnet with given interrelations is a unit of the network.Based on this model dynamic operations:loading and reducing are given,multiple complex networks could be composited and one complex network could be decomposed into multiple complex network by network operations of this model.Secondly,interactions between multiple relationships or nodes in the network and the transmission of these interactions is reflected by signaling process,which can be reflected through importance matrix iteration algorithm.The experimental results on Douban,which is a representative multi-relationship online social network in China,show that the new algorithm improves iteration times and coverage comparing with traditional important node detection algorithms in online social network.The algorithm can improve efficiency and accuracy of the analysis of public opinions,community structure detection and information propagation in online social network.

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