Research Of Influence Maximization In Online Social Networks For Rumors Control

The vigorous development of online social networks has brought a far-reaching impact on human life.Human beings enjoy various online social network services,but also suffer from the impact of online rumors and other issues.The wanton spread of online rumors can easily lead to public panic.How to correctly understand the propagation rules of online rumors,and effectively control the spread of online rumors,has very important social significance.This paper focuses on the problem of the spread of rumors in online social networks.Based on the detailed analysis of the classic epidemic spreading model,this paper divides the infected state into Credulous(C),Neutrals(N)and Denies(D)according to the characteristics of online social networks,then proposes the new SCNDR rumor propagation model in online social networks.Based on the SCNDR model,derives the dynamic differential equations and designs the algorithm for SCNDR.Based on a real online social network rumors spread data analysis results,we verify the effectiveness and applicability of the SCNDR model.Based on the analysis results of SCNDR model,this paper proposes a HCIG influence maximization algorithm in online social networks for rumors control.HCIG algorithm used the idea of hybrid algorithm,combined with the advantages of the greedy algorithm and heuristic algorithm.In the first stage,HCIG algorithm selects the seed nodes in the network on the basis of comprehensive influence CI value.The calculation of CI value is a combination of three factors:the valuable-outdegree of nodes,the penetration influence of nodes and the influence between nodes.At the same time,we optimized the calculation method of buv and used the method of marking to reduce the impact of influence-overlapping between adjacent seed nodes.In the second stage,HCIG algorithm uses greedy algorithm to select the rest of the seed nodes.Therefore HCIG algorithm can get greater influence scope,and the algorithm complexity is lower.This paper selects multiple data sets for simulation between HCIG algorithm and other classic algorithm.The simulation results show that the HCIG algorithm is more efficient and can get greater influence scope.Therefore,in order to solve the problem of rumor spreading,at the beginning of the outbreak of rumors,we should use HCIG algorithm to select seed nodes from networks rapidly and accurately.Then we can release the real and effective information through the selected seed nodes,so as to curb the spread of rumors.