Research On Key Node Selection Methods For Rumor Blocking In Online Social Networks

With the advancement of technology and the rapid rising of the Internet,Online Social Networks(OSNs)such as Twitter,Facebook and emerging Tik Tok have come to the broad masses of people.Providing with many convenient functions such as interaction,resource sharing and online shopping,OSNs have been the mainstream media for people to engage in various social activities in modern era.In addition,the development of OSNs has also brought new research subjects for scholars in Informatics,Psychology,Sociology,Computer Science and other fields.Specifically,information propagation mechanism,psychological tendency analysis of users' shopping behavior,the management and control of public emergency,community detection and data mining and processing OSNs have drawn more and more attention.In summary,OSNs do have great research significance and value.However,due to the openness and the convenience of OSNs,rumors and other bad information can also spread rapidly,which tends to affect social order and social stability.For example,various rumors about COVID-19 in 2020 have seriously affected its prevention and control.Therefore,the study of diffusion of rumor diffusion and blocking has become a common concern of the whole society.In fact,as for the complexity of the topology structure of OSNs,the human beings and other uncertain factors in the process of rumor diffusion,the existing studies on these aspects have different breakthrough points.Considering the characteristics of network topology structure and the identities of OSNs,this paper proposes two methods to select and block the key nodes in the process of rumor diffusion in order to reduce the negative effects it brought.The concrete contents are as follows:1)A method for selecting key nodes based on user blocking tolerance.In real life,it can be found that the users on OSNs have an interesting common characteristic.For the ordinary users,there is a marginal difference between the number of their followers and the number of users followed by them.For the influential users,this difference is huge.Therefore,considering that the influence of users can be measured by the gap between the number of their followers and the number of users followed by them,the influential nodes selection method is proposed based on information entropy.In addition,out of the consideration that direct blocking of top influential users in the network may cause the dissatisfaction of their followers and further lead to greater network disturbances,the concept of user blocking tolerance is proposed in this paper and its value is inversely correlated with the influence of the users.Each user in OSNs will have a tolerance threshold,which represents the critical value of rumor blocking tolerance.It can be blocked only when its user blocking tolerance is not more than the threshold.In general,this method is to select the nodes to be blocked within the user's tolerance for blocking,so as to block the rumor without affecting the user experience.2)A method for selecting blocking nodes based on structural holes.In fact,whether positive information or negative information such as rumors,their diffusion process is closely related to the network topology.In other words,whether a user is infected or not is related to its neighbors.If a user's neighbor misbelieve the rumors and they have close relationship with each other,there will be a high probability for him believing in the rumors.Therefore,a new concept named relationship quality is defined to measure the degree of intimacy between nodes,and a new model to describe the rumor diffusion process in OSNs is built based on it.In addition,the nodes located in the structure holes have a great "power" or influence in the OSNs,which could play an essential part in the diffusion process of rumors.Therefore,four measurement indexes of structural hole theory are introduced and analyzed in this work.Through these four measurements,influential nodes are selected to blocking rumors for preventing their worse influence.Finally,the dynamic blocking method and the one-time blocking method are used to compare the changes of rumor infection ratio in the network after different blocking node selection strategies are adopted.