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一种真假信息传播能力评估的动态规划算法 被引量:2

Dynamic Programming Algorithm for True and False Information Diffusion Ability
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摘要 随着互联网的快速发展,各种社交平台在帮助人们获取信息的同时,也为虚假信息的扩散提供了途径.大量虚假信息的爆发式传播不仅危害了公众的利益,而且为社会稳定带来了巨大的风险.针对社交网络中的真假信息传播模型,一种基于动态规划的计算方法在文章中被提出,该方法通过计算网络中每个节点的近似传播概率对整个网络的信息传播能力进行评估,避免了传统基于蒙特卡罗仿真方法中实验效率和结果精度难以平衡的问题.文章中的实验部分将本文提出的算法与基于蒙特卡罗的仿真方法进行了对比,结果表明该算法在对真假信息的传播能力做出有效评估的同时,大幅度提升了计算效率,为研究不同拓扑结构对真假信息的传播影响和寻找最优信息过滤能力的网络结构提供了便捷的途径. With the rapid development of the Internet,people share information and ideas on various social platforms,which also provide w ays for the dissemination of false information.The large-scale cascading propagation of fake messages will do harm to the public and bring incalculable risks to social stability.For the information diffusion model in the social network,a dynamic programming algorithm for evaluating the true and false information diffusion abilityhas been proposed in this paper.This method estimates the filtering ability by calculating the approximate propagation probability of each node in the netw ork.It avoids the problem of the difficult balance betw een experimental efficiency and accuracy of results in the traditional Monte Carlo simulation method.We conducted comparative analyses of the two methods.The results show that the proposed method can effectively evaluate the filtering ability of the social netw ork w hile improving computing efficiency.It provides convenience to study the impact of different typologies on the spread of messages and find netw ork structure with optimal information filtering ability.
作者 俞山青 郑钧 殳欣成 阮中远 YU Shan-qing;ZHENG Jun;SHU Xin-cheng;RUAN Zhong-yuan(College of Information Engineering,Zhejiang University of Technology,Hangzhou 310000,China;College of Computer Science and Technology,Zhejiang University of Technology,Hangzhou 310000,China)
出处 《小型微型计算机系统》 CSCD 北大核心 2021年第1期85-90,共6页 Journal of Chinese Computer Systems
基金 国家自然科学基金项目-青年(11605154)资助 浙江省基础公益研究计划项目(LGF20F020016)资助。
关键词 社交网络 信息传播 真假信息 传播概率 动态规划 social network information diffusion true and false information propagation probability dynamic programming
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  • 1Domingos P, Richardson M. Mining the network value of cus- tomers[C]//7th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD). San Francisco, CA, 2001 : 57-66.
  • 2Domingos P,Richardson M. Mining knowledge-sharing sites for viral marketing[-C']//The 8th ACM SIGKDD International Con- ference on Knowledge Discovery and Data Mining (KDD). Ed- monton, Canada, 2002 : 61-70.
  • 3Kempe D, Kleinberg J M, Tardos . Maximizing the spread of in- fluence through a social networkI-C/,/The 9th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Washington, DC, 2003 : 137-146.
  • 4Leskovec J, Krause A, Guestrin C, et al. Cost-effective outbreak detection in networksEC]//The 13th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). San Jose, California, 2007 .. 420-429.
  • 5Chen W, Wang Y, Yang S. Efficient influence maximization in social networksrC] ff The 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Paris, France, 2009z 199-207.
  • 6Chen W,Wang C,Wang Y. Scalable influence maximization for prevalent viral marketing in large scale social networksEC]/// The 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD). Washington, DC, 2010 : 1029-1038.
  • 7Chen W, Yuan Y, Zhang L. Scalable influence maximization in social networks under the linear threshold modell-C]ffThe 2010 IEEE International Conference on Data Mining (ICDM). Syd- ney, Australia, 2010 .- 88-97.
  • 8Habiba, Berger- TWolf. Maximizing the extent of spread in a dy- namic network[-R]. Technical Report 20. DIMACS, 2007.
  • 9Even-Dar E,Shapira A. A note on maximizing the spread of in- fluence in social networks[-C']ffWINE 2007. LNCS 4858,2007 281-286.
  • 10Lahiri M, Cebrian M. The genetic algorithm as a general diffu- sion model for social networks[-C]//The Twenty-Fourth AAAI Conference on Artificial Intelligence. Atlanta, Georgia, 2010.. 494-499.

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