计算机科学 ›› 2016, Vol. 43 ›› Issue (12): 41-45.doi: 10.11896/j.issn.1002-137X.2016.12.007

• 智能信息处理 • 上一篇    下一篇

基于行为分析的微博传播模型研究

郑志蕴,郭芳,王振飞,李钝   

  1. 郑州大学信息工程学院 郑州450001,郑州大学信息工程学院 郑州450001,郑州大学信息工程学院 郑州450001,郑州大学信息工程学院 郑州450001
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受郑州大学新媒体公共传播学科招标课题阶段性成果(XMTGGCBJSZ05),河南省科技攻关项目(142102310531)资助

Study on Microblog Propagation Model Based on Analysis of User Behavior

ZHENG Zhi-yun, GUO Fang, WANG Zhen-fei and LI Dun   

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

摘要: 随着微博的迅速兴起和其影响力的不断提高,提取微博信息传播特征和构建传播模型已成为了研究热点。针对用户转发行为,首先分析了信息传播机制;然后从影响用户转发行为的发布用户、接收用户、用户亲密度和信息时效性4个方面提取出8个特征因素进行建模;在借鉴传染病动力学SIR模型的基础上,引入用户行为分析和接触节点,提出基于用户行为分析的SCIR模型,并给出动力学方程;最后利用新浪微博真实转发数据验证模型的合理性。实验结果表明,考虑用户转发行为的8个影响因素,结合行为分析结果,能够较好地拟合信息传播过程。

关键词: 微博,传播,SCIR模型,行为分析

Abstract: With the rapid rise of twitter and its influence continuing to improve,extracting the microblog information dissemination characteristics and building the propagation model have become a hot research topic.Forward for user behavior,firstly the information transmission mechanism was analyzed.Then accroding to eight factors extracted from publishing user,receiving user,user intimacy and information timeliness four aspects which affect the user behavior,the model was established.After that,the SCIR model was presented based on user behavior analysis and its dynamic equation was given.Finally the rationality of the model was validated by real forwarding data.Results show that forward considering user behavior influence factor,and combining the behavior analysis,can well fit information dissemination process.

Key words: Microblog,Propagation,SCIR model,Analysis of behavior

[1] Yuan Wei-guo,Liu Yun,Cheng Jun-jun,et al.Empirical analysis of microblog centrality and spread influence based on Bi-directional connection[J].Acta Physica Sinica,2013,2(3):502-511(in Chinese) 苑卫国,刘云,程军军,等.微博双向“关注”网络节点中心性及传播影响力的分析[J].物理学报,2013,2(3):502-511
[2] Zhang Yang,Lu Rong,Yang Qing.Predicting Retweeting in Microblogs[J].Journal of Chinese Information Processing, 2012,6(4):109-114(in Chinese) 张旸,路荣,杨青.微博客中转发行为的预测研究[J].中文信息学报,2012,6(4):109-114
[3] Qi Chao,Chen Hong-chang,Yu Yan.Micro-blog informationdiffusion effect based on behavior analysis[J].Journal of Computer Applications,2014,4(8):2404-2408(in Chinese) 齐超,陈鸿昶,于岩.基于行为分析的微博信息传播效果[J].计算机应用,2014,4(8):2404-2408
[4] Yi Lan-li.Research on Statistical Characteristic Analysis andModeling for Behavior in Microblog Community Based on Human Dynamics[D].Beijing:Beijing University of Posts and Telecommunications,2012(in Chinese) 易兰丽.基于人类动力学的微博用户行为统计特征分析与建模研究[D].北京:北京邮电大学,2012
[5] Zhou Dong-hao,Han Wen-bao.DiffRank:A Novel Algorithmfor Information Diffusion Detection in Social Networks[J].Chinese Journal of Computers,2014,7(4):884-893(in Chinese) 周东浩,韩文报.DiffRank:一种新型社会网络信息传播检测算法[J].计算机学报,2014,7(4):884-893
[6] Zhang Yan-chao,Liu Yun,Zhang Hai-feng,et al.The Research of Information Dissemination Model on Online Social Network[J].Acta Physica Sinica,2011,0(5):66-72(in Chinese) 张彦超,刘云,张海峰,等.基于在线社交网络的信息传播模型[J].物理学报,2011,0(5):66-72
[7] Chen Qian-guo,Zhang Zi-li.Dynamics Behavior and ImmuneControl Strategies of SIRS Model with Immunization on Scale-free Complex Networks[J].Computer Science,2013,0(6):211-214(in Chinese) 陈乾国,张自力.无标度网络上带人工免疫的SIRS模型动力学行为及其免疫控制策略[J].计算机科学,2013,0(6):211-214
[8] Yang Zi-long,Huang Shu-guang,Wang Zhen,et al.Study onMicro Blog Reposting Model Based on Characteristics of Information Obsolescence[J].Computer Science,2014,1(12):82-85(in Chinese) 杨子龙,黄曙光,王珍,等.基于信息老化特征的微博传播模型[J].计算机科学,2014,1(12):82-85
[9] Gu Yi-ran,Xia Ling-ling.The Propagation and Inhibition of Rumors in Online Social Network[J].Acta Physica Sinica, 2012,1(23):238701(in Chinese) 顾亦然,夏玲玲.在线社交网络中谣言的传播与抑制[J].物理学报, 2012,1(23):238701
[10] Wang Hui,Han Jiang-hong,Deng Lin,et al.Dynamics of Rumor Spreading in Mobile Social Networks[J].Acta Physica Sinica, 2013,2(11):110505(in Chinese) 王辉,韩江洪,邓林,等.基于移动社交网络的谣言传播动力学研究[J].物理学报,2013,2(11):110505
[11] Cha M,Haddadi H,Benevenuto F,et al.Measuring user inf-luence in twitter:the million follower fallacy [C]∥Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media(ICWSM 2012).Menlo Park:AAAI Press,2010:10-17
[12] Crandall D,Cosley D,Huttenlocher D,et al.Feedback effectsbetween similarity and social influence in online communities[C]∥Proceeding of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.Las Vegas,USA,ACM,2008:160-168
[13] Singla P,Richardson M.Yes,there is a correlation:From social networks to personal behavior on the Web[C]∥Proceeding of the 17th International World Wide Web Conference.Beijing,China,2008:665-664
[14] Mao Jia-xin,Liu Yi-qun,Zhang Min,et al.Social Influence Anal-ysis for Micro-Blog User Based on User Behavior[J].Chinese Journal of Computers,2014,7(4):791-795(in Chinese) 毛佳昕,刘奕群,张敏,等.基于用户行为的微博用户社会影响力分析[J].计算机学报,2014,7(4):791-795
[15] Kwak H,Lee C,Park H,et al.What is Twitter,a social network or a news media? [C]∥Proceddings of the 19th international conference on World Wide Web.ACM,2010:591-600
[16] Newman M.Network:an introduction [M].New York:Oxford University Press,2009:449
[17] Li He-yuan,Yu Xiao-ming,Liu Yue,et al.Research on Detecting Spammer in Micro-blogs[J].Journal of Chinese Information Processing,2014,8(3):62-67(in Chinese) 李赫元,俞晓明,刘悦,等.中文微博客的垃圾用户检测[J].中文信息学报,2014,8(3):62-67

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!