Two Stage Rumor Blocking Method Based on EHEM in Social Networks

Therise of online social networks has brought about a series of challenges and risks,including the spread of false and malicious rumors,which can mislead the public and disrupt social stability.Therefore,blocking the spread of rumors has become a hot topic in the field of social networks.While significant efforts have been made in rumor blocking,there still exist limitations in accurately describing information propagation in social networks.To address this issue,this paper proposes a novel model,the extended heat energy model(EHEM),to characterize information propagation.EHEM fully takes into consideration several key aspects of information propagation,including the dynamic adjustment mechanism of node activation probabilities,the cascading mechanism of information propagation,and the dynamic transition mechanism of node states.By incorporating these factors,the EHEM provides a more precise representation of the explosive and complex nature of information propagation.Furthermore,ta-king into account the possibility of belief transition from rumors to truth for nodes that initially believe in rumors in the real world,this paper introduces a correction threshold to determine whether a node undergoes belief transformation.Additionally,the importance of nodes determines their influence spreading.Therefore,a multidimensional quality measure of nodes is proposed to assess their importance.Finally,a two stage rumor containment(TSRC) algorithm is proposed,which first prunes the network using the multidimensional quality measure of nodes and then selects the optimal set of positive seeds through simulations.Expe-rimental results on four real-world datasets demonstrate that the proposed algorithm outperforms six other comparative algorithms,including Random,Betweenness,MD,PR,PWD,and ContrId on multiple metrics.