| In recent years,with the rapid development of Internet technology and the popularization of mobile terminals,online social networking platforms represented by Weibo and WeChat,etc.have become an important medium for information dissemination and sharing,and have gathered a large user group,and have constituted a huge information transmission network by the extremely high real-time and the extremely strong transmissibility.The rapid advancement of mankind into the age of self-media has provided convenience to people's lives,injected new vitality into social production and played a huge role in improving the national economy and promoting social development.Therefore,to explore the internal law and mechanism of online social network information dissemination,and to analyze the characteristics of information dissemination and the factors affecting the dissemination,is an important prerequisite for effective management of bad information in the network.Many scholars domestic and overseas have conducted in-depth research on information dissemination and control problems in online social networks and have achieved many achievement.Based on previous researches,this paper makes further research on information dissemination and control in online social networks.The main contents are as follows:(1)Consider the situation that the information is not transmitted in time after the user gets it in the actual transmission,this paper introduces an informed node C based on the classic SIR model,and builds a SCIR propagation model affected by neighb or nodes and the timeliness of information.As users will produce their own subjective cognition after receiving the information,which is the attitude value of whether they tend to spread the information,and the attitude value will be dynamically changed by the influence of neighbor nodes.The non-Bayesian social learning method is used to describe the update situation of user's attitude value,then makes the model have a better fit and adaptability and be closer to the propagation characteristics and rul es of actual network by defining the state transformation probability function between different users.Finally,BA,WS,Twitter,sina weibo and other networks are taken as the base graph to build the propagation model under the corresponding network,and compare the process of information transmission in different network environments.The simulation results show that the information timeliness and neighbor nodes have important effects on the propagation process,the information propagation speed of Twitter network is faster than that of Sina network,and the conclusions on the network cannot be covered entirely by information.(2)Consider the rampant spread of rumors on online social networks.Based on the prior knowledge,Multi-Agent is used to model the rumor propagation process and analyze the main factors affecting the rumor propagation on the basis of prior knowledge.First of all,the influence of the social conformity effect on rumor propagation is described from the local environment,and the transformation trend of users' behavioral consciousness in the process of rumor propagation is taken as the entry point of the influence degree of rumor propagation,and the influence of social conformity effect on the process and degree of rumor propagation is an alyzed from the micro and macro perspectives.Then,rumor dispelling mechanism is added to the model to analyze the changes of rumor disseminators and the development trend of rumors under releasing rumor refuting information in different times and credibi lity.Finally,the AnyLogic simulation platform is built for simulation experiments.The results show that the social conformity effect will accelerate the spread of rumors and expand the influence scope of rumors.The earlier the government and mainstream media with strong credibility publish rumor refutation information,the sooner they can control the transformation rate of propagation nodes in unit time,reduce the propagation scale of rumors and delay the outbreak of rumors. |
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