Computer Science ›› 2014, Vol. 41 ›› Issue (12): 82-85.doi: 10.11896/j.issn.1002-137X.2014.12.018

Previous Articles     Next Articles

Study on Micro Blog Reposting Model Based on Characteristics of Information Obsolescence

YANG Zi-long,HUANG Shu-guang,WANG Zhen,LI Yong-cheng and XIAO Jia   

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

Abstract: With the rapid development of the micro blog,extracting the characteristics of the message propagation and constructing the propagation model have already been a hot topic.Focused on users’ reposting behavior,first we analyzed the structure of the message reposting and extracted the characteristics of information obsolescence.Then we proposed an improved SIR model based on the law of diminishing reposting probability combining the time-effectiveness of the message.At last,we made use of real reposting data to prove the validity of our model.The results show that taking the time-effectiveness and information obsolescence of message into account can fit the progress of the message propagation well.Furthermore,we took advantage of this model to analyze the scale-free property of the vertex influence distribution.

Key words: SIR model,Reposting length,Characteristics of reposting,Information obsolescence,Sina micro blog

[1] Grabowski A,Kosinski R A.Percolation in Real On-line Networks[J].Acta Physica Polonica B,2010,1(5):1135
[2] 郑蕾,李生红.基于微博网络的信息传播模型[J].通信技术,2012,5(2):39-41
[3] 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
[4] Ye Shao-zhi,Wu Fe-lix.Measuring Message Propagation andSocial Influence on Twitter.Com[C]∥Proceedings of the Se-cond International Conference on Social Informatics.Springer Berlin Heidelberg,2010:216-231
[5] Kwak H,Lee C,Park H,et al.What is Twitter,a social network or a news media?[C]∥Proceedings of the 19th international conference on World Wide Web.ACM,2010:591-600
[6] Java A,Song Xiao-dan,Finin T,et al.Why We Twitter:Understanding Microblogging Usage and Communities[C]∥Procee-dings of the 9th Webkdd and 1st Sna-kdd 2007 Workshop on Web Mining and Social Network Analysis.ACM,2007:56-65
[7] 陈慧娟,郑啸,陈欣.微博网络信息传播研究综述[J].计算机应用研究,2014(2):333-338
[8] Yang Zi,Guo Jing-yi,Cai Ke-ke,et al.Understanding Retwee-ting Behaviors in Social Networks[C]∥Proceedings of the 19th ACM International Conference on Information and Knowledge Management.ACM,2010:1633-1636
[9] Suh Bong-won,Hong Li-chan,Pirolli P,et al.Want to beretweeted? large scale analytics on factors impacting retweet in twitter network[C]∥2010 IEEE Second International Conference on Social Computing (SocialCom).IEEE,2010:177-184
[10] 李英乐,于洪涛,刘力雄.基于SVM的微博转发规模预测方法[J].计算机应用研究,2013,0(9):2594-2597
[11] 于晶,刘臣,单伟.在线社会网络中信息传播的结构研究[J].情报科学,2013,1(12):136-140
[12] 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
[13] 熊熙,胡勇.基于社交网络的观点动力学研究[J].物理学报,2012,1(15):104-110
[14] Xiong Fei,Liu Yun,Zhang Zhen-jiang,et al.An Information Dif-fusion Model Based on Retweeting Mechanism for Online Social Media[J].Physics Letters A,2012,6(30):2103-2108
[15] 李慧.从文献信息老化到网络信息老化的研究分析[J].情报科学,2010,8(3):384-388,394
[16] 龚思婷,孙建军.网络信息生命力评价——基于网络信息的增长与老化模型[J].情报杂志,2012,1(5):75-79
[17] 沈珂轶.社会网络的社团发现与动态特性研究[D].上海:上海交通大学,2011
[18] Bakshy E,Hofman J M,Mason W A,et al.Everyone’s an Influencer:quantifying Influence on Twitter[C]∥Proceedings of the Fourth ACM International Conference on Web Search and Data Mining.ACM,2011:65-74
[19] Newman M.Network:an introduction [M].New York:Oxford University Press,2009:449
[20] 刘志明,刘鲁.微博网络舆情中的意见领袖识别及分析[J].系统工程,2011,9(6):8-16
[21] 肖宇,许炜,商召玺.微博用户区域影响力识别算法及分析[J].计算机科学,2012,9(9):38-42
[22] Weng J,Lim E P,Jiang J,et al.Twitterrank:Finding Topic-sensitive Influential Twitterers [C]∥Proceedings of the Third Acm International Conference on Web Search and Data Mining.ACM,2010:261-270

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!