计算机科学 ›› 2021, Vol. 48 ›› Issue (3): 313-319.doi: 10.11896/jsjkx.200400079
袁得嵛1,2, 陈世聪1, 高见1,2, 王小娟3
YUAN De-yu1,2, CHEN Shi-cong1, GAO Jian1,2, WANG Xiao-juan3
摘要: 在新冠肺炎疫情期间,社交媒体以前所未有的速度向全世界传播消息。然而,扭曲信息隐藏在海量社交数据中,对国家安全、社会稳定提出了前所未有的挑战。目前的干预措施大多是建立在对关键节点和关键链路进行控制的基础之上,即删帖和封号,往往效果不佳且容易产生副作用。基于扭曲信息的定义和分析,打破传统思维的限定,在信息蔓延过程中通过发布辟谣信息来干扰扭曲信息的演化过程。借助斯塔克尔伯格博弈理论,文中通过设置奖励来鼓励更多的社交网络用户参与信息对冲过程,从而阻止扭曲信息的爆发效应。基于所提出的斯塔克尔伯格博弈模型,分析了斯塔克尔伯格博弈均衡解的存在性和唯一性,并从理论上推导出斯塔克尔伯格博弈的闭式均衡解,提出了基于最优策略的扭曲信息干预算法。实际网络中的仿真实验表明,相比传统的基于网络结构的免疫策略以及其他基于博弈论的干预算法,所提算法最高可将扭曲信息的传播范围分别降低41%和9%,因此能够有效抑制扭曲信息的传播。
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