融合用户传播风险和节点影响力分析的虚假信息传播控制方法OA北大核心CSTPCD

The spread of disinformation on online social networks(OSNs)has become a critical challenge for cyber-space security governance.This paper presents DDC-UPRNI,a disinformation diffusion control method,by integrating user propagation risk with node influence analysis.First,comprehensively considering the diversity and complexity of the characteristic space of disinformation propagation,an embedded representation of the behavior,time and content di-mensions of user propagation of disinformation is realized through the self-attention mechanism,and the automatic clas-sification of different user propagation risk levels is achieved using the improved unsupervised clustering K-means++ algorithm.Second,an adaptive weighting strategy is designed to improve the discrete particle swarm optimization al-gorithm,and a method for selecting key nodes of disinformation propagation is proposed based on the discrete particle swarm optimization.This method determines several influential control driving nodes from the user node set with a spe-cific propagation risk level to achieve accurate and highly efficient disinformation propagation control.Finally,experi-ments are performed on a real OSN platform,and the results demonstrate that the proposed DDC-UPRNI method has obvious advantages over other existing algorithms in some important indicators,including control effect and time com-plexity.This method provides a significant reference value for the current governance of disinformation in social cyber-space.