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基于行为预测的微博网络信息传播建模 被引量：32

Modeling information diffusion based on behavior predicting in microblog
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摘要 研究微博网络中的信息传播及扩散机制在市场营销、舆情管控等方面具有重要意义。当前的传播模型大多忽视了用户间的个体差异。为解决这一问题,提取了影响转发行为的四类特征,利用机器学习中的逻辑回归模型分析预测个体转发行为,并在此基础上融入用户个体差异,建立了一种基于行为预测的信息传播模型。实验表明,该模型能较好地模拟真实网络中的信息传播过程。 Studying the information diffusion model in microblog is necessary in many different fields such as viral marketing.The most current diffusion models ignored the diversity of different users.This paper used logistic regression model to predict user＇s retweet behavior and then built a information diffusion model.Simulation result illustrates that this model can forecast the trend of information diffusion well.
作者 吴凯 季新生 刘彩霞
机构地区 国家数字交换系统工程技术研究中心
出处 《计算机应用研究》 CSCD 北大核心 2013年第6期1809-1812,共4页 Application Research of Computers
基金 国家"863"计划资助项目(2011AA7116011 2011AA010604)
关键词 微博 转发 行为预测 信息传播建模 microblog retweet behavior prediction information diffusion model
分类号 TP393 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献9

  • 1王晶,朱珂,汪斌强.基于信息数据分析的微博研究综述[J].计算机应用,2012,32(7):2027-2029. 被引量：21
  • 2LESKOVEC J, McGLOHON M, FALOUTSOS C, et al. Cascading behavior in large blog graphs patterns and a model[ C]//Proc of the Society of Applied and Industrial Mathematics: Data Mining. 2007:551-556.
  • 3GRUHL D, GUHA R, LIBEN-NOVELL D, et al. Information diffusion through blogspace[ C ] //Proc of the 13th International Conference on World Wide Web. New York:ACM Press,2004:491-501.
  • 4NARAYANAM R, NARAHAR! Y. A shapley value-based approach to discover influential nodes in social networks[ J]. IEEE Trans on Automation Science and Engineering ,2011,20( 1 ) :130-147.
  • 5LAHIRI M, CEBRIN M. The genetic algorithm as a general diffusion model for social networks [ C ]//Proc of the 24th AAAI Conference on Artificial Intelligence. 2010:494 - 499.
  • 6赵丽,袁睿翕,管晓宏,贾庆山.博客网络中具有突发性的话题传播模型[J].软件学报,2009,20(5):1384-1392. 被引量：35
  • 7SUH B, HONG Li-chan, PIROLLI P, et al. Want to be Retweeted? Large scale analytics on factors impacting retweet in twitter network [ C ]//Proc of IEEE International Conference on Social Computing. 2010 : 177-184.
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  • 9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,2012,26(4):109-114. 被引量：70

二级参考文献41

  • 1Kumar R, Novak J, Raghavan P, Tomkins A. On the bursty evolution of blogspace. In: Proc. of the 12th Int'l Conf. on World Wide Web. New York: ACM Press, 2003. 159-178.
  • 2China Internet Network Information Center. Research report of 2007 China blog market. Statistical Report, 2007 (in Chinese). http://www.cnnic.net.cn/html/Dir/2007/12/26/4948.htm
  • 3China Internet Network Information Center. Research report of 2006 China blog. Statistical Report, 2006 (in Chinese). http://www.cnnic.net.cn/html/Dir/2006/09/25/4176.htm
  • 4Zhao ZL. A clear thinking toward the prosperity of blog: A disseminative understanding of news biog. Journal of Nanjing University of Posts and Telecommunications (Social Science), 2006,8(2):23-26
  • 5Qu H. "Alienation" of online community and media. Southeast Communication, 2006,(3):45-47
  • 6Kumar R, Novak J, Raghavan P, Tomkins A. Structure and evolution of blogspace. Communications of the ACM, 2004,47(12): 35-39.
  • 7Adar E, Zhang L, Adamic LA, Lukose RM. Implicit structure and the dynamics of blogspace. In: Proc. of the Workshop on the Weblogging Ecosystem, the 13th Int'l World Wide Web Conf. New York: ACM Press, 2004.
  • 8Adar E, Adamic LA. Tracking information epidemics in blogspace. In: Proc. of the 2005 IEEE/WIC/ACM Int'l Conf. on Web Intelligence. Compiegne: IEEE Computer Society Press, 2005. 207-214.
  • 9Leskovec J, McGlohon M, Faloutsos C, Glance N, Hurst M. Patterns of cascading behavior in large blog graphs. In: Proc. of the SIAM Int'l Conf. on Data Mining. New York: ACM Press, 2007. 551-556.
  • 10Gruhl D, Guha R, Liben-Nowell D, Tomkins A. Information diffusion through blogspace. In: Proc. of the 13th Int'l Conf. on World Wide Web. New York: ACM Press, 2004.491-501.

共引文献119

同被引文献384

引证文献32

二级引证文献250

计算机应用研究
2013年 第6期

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