摘要
传统在线社交网络谣言分析模型均考虑单一的社交网络,而当前谣言通常跨多个社交网络进行传播,传播速度极快,影响极大。针对这种情况,提出一种基于社交影响力的跨多个社交网络谣言传播模型,基于该模型给出贪婪谣言抑制方法。通过用户与其邻居的外部聚类系数决定社交网络的影响力节点,保留高影响力节点的谣言扩散连接,从而降低模型的复杂度,以贪婪算法为基础,预测传播能力强的种子节点,通过失活种子节点集对谣言进行快速抑制。实验结果表明,该模型能够较为准确地模拟谣言的传播趋势,同时算法能够快速抑制谣言的传播。
The rumor detection and analysis models for traditional online social networks are designed for single social platform,but current rumors usually spread across multiple social networks,which leads to fast spread and large influence.In view of this,We propose a rumor spread model across multiple social networks based on social influences,also present a greedy rumor reduce method based on the model.The model decided the influential nodes for social networks through the external clustering coefficients between the special node and it s neighbors,then it retained rumor diffusion links of influential nodes to reduce the complexity of the model.The method predicted the seed nodes with strong spread capacity,and reduced the rumor spreading through disabling seed nodes based on the greedy algorithm.Experimental results show that this model can simulate the trend of rumor spread accurately,and the proposed algorithm can reduce rumor spread effectively.
作者
郭宏刚
杨芳
Guo Honggang;Yang Fang(College of Computer and Cyber Security,Hebei Normal University,Shijiazhuang 050024,Hebei,China;Key Laboratory of Network&Information Security,Hebei Normal University,Shijiazhuang 050024,Hebei,China;Hebei Provincial Engineering Research Center for Supply Chain Big Data Analytics&Data Security,Shijiazhuang 050024,Hebei,China;Department of Police Scientific Research,Hebei Vocational College of Public Security Police,Shijiazhuang 050091,Hebei,China)
出处
《计算机应用与软件》
北大核心
2022年第7期73-79,153,共8页
Computer Applications and Software
基金
河北省社会科学发展研究课题项目(20200302089)
河北省教育厅课题项目(ZC2022112)。
关键词
在线社交网络
网络安全
公共安全
谣言传播
贪婪算法
Online social networks
Network security
Public security
Rumor spread
Greedy algorithm
