太原理工大学学报2025，Vol.56Issue(5)：887-896,10.DOI:10.16355/j.tyut.1007-9432.20240227
多结构与属性融合的谣言传播关键节点识别
Identification of Key Nodes in Rumor Propagation with Multi-structure and Attribute Fusion
摘要
Abstract
[Purposes]How to quickly and accurately identify key rumor nodes has become an im-portant challenge in current research.Existing studies usually use centrality methods based on network structure or machine learning methods based on node features to identify key nodes.However,most of these methods are based on the idea of information spreading,ignoring the unique way of rumor propagation.Centrality methods fail to fully reflect the actual importance of nodes in rumor propaga-tion,that means nodes with high centrality may not play key roles in rumor propagation,while ma-chine learning methods tend to ignore the structural information of rumor propagation.[Methods]To address the above problems,in this paper,a RumorGFAN model that integrates the rumor propaga-tion structure,information propagation structure,and user attribute information was proposed for iden-tifying key rumor nodes in rumor propagation process.In addition,individual behavioral differences in rumor propagation were considered,after receiving a rumor,some individuals may may to spread it while others may not,Besides,the susceptible-exposed-infected-recovered-susceptible(SEIRS)model that is more consistent with rumor propagation was adopted,and a new computational method was proposed to assess the influence of nodes more accurately.[Results]Experimental results on four real datasets of different sizes show that this strategy is able to identify key rumor nodes in online so-cial networks more accurately and efficiently.关键词
社交网络/关键谣言节点/节点识别/谣言传播Key words
social network/key rumor nodes/node identification/rumor propagation分类
信息技术与安全科学引用本文复制引用
李琪,许晓雅,王莉..多结构与属性融合的谣言传播关键节点识别[J].太原理工大学学报,2025,56(5):887-896,10.基金项目
国家自然科学基金区域创新发展联合基金(U22A20167) （U22A20167）
国家重点研发计划(2021YFB3300503) （2021YFB3300503）
