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复杂系统与复杂性科学  2014, Vol. 11 Issue (4): 54-60    DOI: 10.13306/j.1672-3813.2014.04.010
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基于小世界网络的微博谣言传播演进研究
刘咏梅1, 彭琳1, 赵振军1,2
1.中南大学商学院,长沙 410012;
2.湖南科技大学管理学院,湖南 湘潭 411201
The Evolution of Rumor Spread on Micrblog Based on Small-World Network
LIU Yongmei1, PENG Lin1, ZHAO Zhenjun1,2
1. School of Business Administration, Central South University, Changsha 410012, China;
2. School of Management, Hunan University of Science and Technology, Xiangtan 411201, China
全文: PDF(1258 KB)  
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摘要 刻画谣言在微博上的快速传播状态,研究影响谣言传播的关键因素。基于传染病的基础模型,将受众扩展为5类(无知者、接触者、传播者、沉寂者、失去兴趣者),引入兴趣衰减系数描述个体多次接触谣言时转发兴趣降低状态,同时考虑了个体只会转发一次的现实状况。为验证模型的有效性,对模型进行了多主体仿真,并将仿真数据与两个真实案例的数据对比,发现构建的模型可以较好地拟合现实情况。通过仿真实验,对不同因素的系数进行对比分析,发现改变兴趣衰减系数、首次转发概率以及小世界网络的属性都显著影响了微博的传播演进过程。
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刘咏梅
彭琳
赵振军
关键词 谣言传播微博小世界网络多主体仿真    
Abstract:This article focuses on the evolution of the rapid rumor spread on the microblog and the key factors affecting the spread of rumors. Based on the model of infectious diseases, expanded the people to the five class (ignorant, infected, contacted, exhausted, resistant), add the coefficient of interest decay to the model, and the individual just can be forward the rumor once. To verify the validity of the model, we made the multi-agent simulation, and made comparison to the simulation data and the data from two real cases. We found the model can be fit reality well. Through simulation experiments, the coefficients of different factors were analyzed and found that the coefficient of interest decay, the first forwarding probability and the properties of small-world networks can significantly affect the evolution of the spread.
Key wordsrumor spread    microblog    small-network    multi-agent simulation
收稿日期: 2013-08-30      出版日期: 2026-06-22
基金资助:国际(地区)合作与交流项目(71210003);教育部“新世纪优秀人才支持计划”(NCET-11-0519);教育部博士点基金项目(20110162110065)
作者简介: 刘咏梅(1969-),女,安徽巢湖人,博士,教授,主要研究方向为团队决策理论与方法、管理信息系统与供应链管理。
引用本文:   
刘咏梅, 彭琳, 赵振军. 基于小世界网络的微博谣言传播演进研究[J]. 复杂系统与复杂性科学, 2014, 11(4): 54-60.
LIU Yongmei, PENG Lin, ZHAO Zhenjun. The Evolution of Rumor Spread on Micrblog Based on Small-World Network[J]. Complex Systems and Complexity Science, 2014, 11(4): 54-60.
链接本文:  
https://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2014.04.010      或      https://fzkx.qdu.edu.cn/CN/Y2014/V11/I4/54
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