王 怡,梁 循,周小平. 基于统计的新浪微博动态传播规律研究[J]. 中文信息学报, 2016, 30(5): 36-46.
WANG Yi, LIANG Xun, ZHOU Xiaoping. A Statistical Analysis of the Propagation Mode in Sina Micorblog. , 2016, 30(5): 36-46.
基于统计的新浪微博动态传播规律研究
王 怡,梁 循,周小平
中国人民大学 信息学院,北京100872
A Statistical Analysis of the Propagation Mode in Sina Micorblog
WANG Yi, LIANG Xun, ZHOU Xiaoping
School of Information, Renming University, Beijing 100872
Abstract:Online Social Networking (OSN) is a complex system, where both users and messages are fundamental objects when investigating the network topology and the disseminations of information. To study the structure features and the rules of information propagation, this paper analyzes about 30,000 users including their friendships and the most recent 200 posts. The main statistical results include: 1) SINA network is not dense and the correlation density is almost linear; 2) during the dissemination of a single post, “10-90 rule” occurs, that is to say 10% of the users can affect the other 90%; and 3) four patterns can be concluded considering both life-cycle and forwarding structure. These results may provide the basis for subsequent modeling, as well as benefition the public opinion monitoring and cyber marketing.
[1] 刘玮,王丽宏,李锐光. 面向话题的微博网络测量研究[J]. 通信学报,2013,11: 171-178.
[2] Magnani M,Montesi D,Rossi L.Information propagation analysis in a social network site[C]//ASONAM.2010: 296-300.
[3] Matsubara Y, Sakurai Y, Prakash B A. Rise and fall patterns of information diffusion: model and implications[C]//Proceedings of 18th ACM SIGKDD Int Conf Knowledge Discovery &Data Mining, 2012: 6-14.
[4] Sadikov E, Martinez M M M. Information propagation on Twitter[R]. CS322 Project Report, 2009.
[5] Sun E, Rosenn I, Marlow C, et al. Gesundheit! Modeling Contagion through Facebook News Feed[C]//ICWSM,2009.
[6] Shaozhi Y E, WU S. Measuring Message Propagation and Social Influence on Twitter. com[C]//Proceedings of the 2nd International Conference on Social Informatics,October.2010: 27-29.
[7] 樊鹏翼,王晖,姜志宏,李沛. 微博网络测量研究[J]. 计算机研究与发展,2012,04: 691-699.
[8] 曹玖新,吴江林,石伟,刘波,郑啸,罗军舟. 新浪微博网信息传播分析与预测[J]. 计算机学报,2014,04: 779-790.
[9] 沈乾,马宁,黄远,刘怡君. 微博传播波的函数解析实证研究[J]. 数学的实践与认识,2014,21: 143-151.
[10] 易成岐,鲍媛媛,薛一波,姜京池. 新浪微博的大规模信息传播规律研究[J]. 计算机科学与探索,2013,06: 551-561.
[11] Ren D, Zhang X, Wang Z, et al. WeiboEvents: a crowd sourcing weibo visual analytic system[C]//Pacific Visualization Symposium (PacificVis), 2014 IEEE. IEEE, 2014: 330-334.
[12] Sadikov E, Martinez M M M. Information propagation on Twitter[J]. CS322 Project Report, 2009.
[13] Ye S, Wu S F. Measuring message propagation and social influence on Twitter. com[M]. Springer Berlin Heidelberg, 2010.
[14] 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.
[15] Guille A, Hacid H. A predictive model for the temporal dynamics of information diffusion in online social networks[C]//Proceedings of the 21st international conference companion on World Wide Web. ACM, 2012: 1145-1152.
[16] Myers S A, Zhu C, Leskovec J. Information diffusion and external influence in networks[C]//Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2012: 33-41.