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CRB:A new rumor blocking algorithm in online social networks based on competitive spreading model and influence maximization

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Chinese Physics B 2024年第8期33卷 588-604页

作者：董晨徐桂琼孟蕾 School of Management Shanghai UniversityShanghai 200444China

The virtuality and openness of online social platforms make networks a hotbed for the rapid propagation of various *** order to block the outbreak of rumor,one of the most effective containment measures is spreading positive information to counterbalance the diffusion of *** spreading mechanism of rumors and effective suppression strategies are significant and challenging research ***,in order to simulate the dissemination of multiple types of information,we propose a competitive linear threshold model with state transition(CLTST)to describe the spreading process of rumor and anti-rumor in the same ***,we put forward a community-based rumor blocking(CRB)algorithm based on influence maximization theory in social *** crucial step is to identify a set of influential seeds that propagate anti-rumor information to other nodes,which includes community detection,selection of candidate anti-rumor seeds and generation of anti-rumor seed *** the CLTST model,the CRB algorithm has been compared with six state-of-the-art algorithms on nine online social networks to verify the *** results show that the proposed model can better reflect the process of rumor propagation,and review the propagation mechanism of rumor and anti-rumor in online social ***,the proposed CRB algorithm has better performance in weakening the rumor dissemination ability,which can select anti-rumor seeds in networks more accurately and achieve better performance in influence spread,sensitivity analysis,seeds distribution and running time.

关键词： online social networks rumor blocking competitive linear threshold model influence maximization

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