计算机科学 ›› 2016, Vol. 43 ›› Issue (10): 135-140.doi: 10.11896/j.issn.1002-137X.2016.10.025

• 信息安全 • 上一篇    下一篇

基于多标签传播的社交网络用户影响力评估

许为,林柏钢,林思娟,杨旸   

  1. 福州大学数学与计算机科学学院 福州350108网络系统信息安全福建省高校重点实验室 福州350108,福州大学数学与计算机科学学院 福州350108网络系统信息安全福建省高校重点实验室 福州350108,福州大学数学与计算机科学学院 福州350108网络系统信息安全福建省高校重点实验室 福州350108,福州大学数学与计算机科学学院 福州350108网络系统信息安全福建省高校重点实验室 福州350108
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金(61402112),福建省安全课题(828398)资助

Assessment of User Influence in Social Networks Based on Multi-label Propagation

XU Wei, LIN Bo-gang, LIN Si-juan and YANG Yang   

  • Online:2018-12-01 Published:2018-12-01

摘要: 为了识别出社交网络中的关键人物,需要对用户影响力进行评估。由于影响力是借助信息在网络中的扩散而逐步形成的,因此需首先对影响力传播过程进行建模;然后以该模型为基础,用标签表示影响力的所有者,以隶属度表示用户被影响的程度,利用多标签传播来模拟影响力传播的过程,实现了一种新的用户影响力评估算法MLPIA(Multi-label Propagation User Influence Asessment Algorithm);最后,在真实数据集上测验排名靠前的用户的影响力覆盖范围和紧密中心性,结果证明了该算法的合理性和有效性。

关键词: 用户影响力,多标签传播,影响力传播,社交网络,效果评判

Abstract: In order to identify the key figures in social networks,we need to assess the user influence.Influence is gra-dually formed on the base of the information propagation.This paper built a model to describe the process of influence propagation.Then,based on the model,we used label to indicate the original owner of influence and used degree of membership to indicate the effect degree of which users are affected.We utilized multi-label propagation to simulate the process of users’ influence propagation to achieve a new user influence assessment algorithm MLPIA (Multi-label Propagation User Influence Assessment Algorithm).Lastly,the coverage area and closeness centrality of top users’ influence were tested on real data set.The results demonstrate the rationality and validity of the proposed algorithm.

Key words: User influence,Multi-label propagation,Influence propagation,Social networks,Effect judgment

[1] Porzycki J,Was J.Novel algorithms of sensors detection in social network.2015-10-23.http://www.researchgate.net/publication/262560387
[2] Yang Kai,Zhang Ning,Su Shu-qing.Node Centrality on Indivi-dual Microblog User Network[J].University of Shanghai for Scien-ce and Technology,2015,37(1):43-48(in Chinese) 杨凯,张宁,苏树清.个人微博用户网络的节点中心性研究[J].上海理工大学学报,2015,37(1):43-48
[3] Wang Xiao-fang,Li Xiang,Chen Guang-rong.Network Science:An Intorduction[M].Beijing:Higher Education Press,2012:158-159(in Chinese) 汪小帆,李翔,陈关荣.网络科学导论[M].北京:高等教育出版社,2012:158-159
[4] Kitsak M,Gallos L K,Havlin S,et al.Identification of influential spreaders in complex networks[J].Nature Physics,2010,6:888-893
[5] Brin S,Page L.The anatomy of a large-scale hypertextual web search engine[J].Computer Networks,1998,30:107-117
[6] Weng J,Lim E P,Jiang J,et al.TwitterRank:finding topic-sensitive influential twitterers[C]∥International Conference on Web Search and Data Mining.2010:261-270
[7] Xu Yang.Researches on the center nodes estimate and community discovery on microblog network[D].Nanning:Guangxi University,2013(in Chinese) 徐杨.微博网络的中心节点评估与社区发现方法研究[D].南宁:广西大学,2013
[8] Wu Xian-hui,Zhang Hui,Yang Chun-ming,et al.An Algorithm of Topic-related Microblogging Opinion Leaders Mining[J].Journal of Chinese Computer Systems,2014,35(10):2296-2301(in Chinese) 吴岘辉,张晖,杨春明,等.一种话题相关的微博意见领袖挖掘算法[J].小型微型计算机系统,2014,35(10):2296-2301
[9] Xiao Yin-tao.Research on Rumor Propagation and Public Opi-nion Mining in Microblogging Community [D].Zhenjiang:Jiangsu University,2011(in Chinese) 萧银涛.微博社区谣言传播和舆情挖掘研究[D].镇江:江苏大学,2011
[10] Gregory S.Finding Overlapping Communities in Networks ByLabel Propagation[J].New Journal of Physics,2010,12(10):2011-2024
[11] Kempe D,Kleinberg J,Tardos é.Influential nodes in a diffusion model for social networks[M]∥Automata,Languages and Programming.Berlin Heidelberg:Springer Berlin Heidelberg,2005:1127-1138
[12] Chen Hao,Wang Yi-tong.Threshold-Based Heuristic Algorithm for Influence Maximization[J].Journal of Computer Research and Development,2015,9(10):2181-2188(in Chinese) 陈浩,王轶彤.基于阈值的社交网络影响力最大化算法[J].计算机研究与发展,2015,49(10):2181-2188
[13] Newman M E J.Scientific collaboration networks.II.Shortestpaths,weighted networks,and centrality[J].Physical Review E,2001,64(1):132-158
[14] Ma Jun,Zhou Gang,Xu Bin,et al.User Influence Analysis in Microblog Based on Topic Diffusion[J].Journal of Information Engineering University,2013,14(6):735-742(in Chinese) 马俊,周刚,许斌,等.一种基于话题传播的微博用户影响力分析方法[J].信息工程大学学报,2013,14(6):735-742

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!