Modeling And Research Of SEIHR Rumor Spreading Model In Complex Social Networks

Rumor,as a special kind of information,disrupts the social order.With the rapid development of computer science and communication technology,besides the traditional face to face communications,people can contact with each other on online networks,such as We Chat and Weibo.It is of great value and practical significance to study the propagation of rumor spreading and control strategy.By considering different attitudes towards rumor,forgetting mechanism,and remembering mechanism of rumor spreading process simultaneously,the SEIHR(Susceptible-Exposed-Infected-HibernatedRemoved)rumor spreading model is modified both on homogeneous networks and heterogeneous networks.The propagation of rumor spreading and control strategy are explored systematically.The steady-state analysis is conducted to obtain the spreading threshold and final rumor size and so on.The Monte Carlo simulations are conducted to verify the theoretical results and investigate the related mechanisms.Based on the model being modified,the efficiency of different immunization strategies is discussed,which can provide theoretical foundations for some related departments to control rumor spreading process.The main work of this thesis includes:(1)The research of modeling rumor spreading process with consideration of human attitudes,forgetting mechanism,and forgetting mechanism.When contacting a rumor,people may agree with it,or disagree with it.In addition,they may be neutral and hesitate to spread or not.People may forget the rumor during the rumor spreading process.On the contrary,they may remember the rumor and spread it.Different from classical rumor spreading model,the SEIHR rumor spreading is modified on homogeneous networks by considering the above factors.The stability of equilibrium point is proved.The threshold of spreading process is derived and final rumor size is obtained.The Monte Carlo simulations are conducted as well.(2)The research of rumor spreading propagation combining the topological characteristics of realworld social networks.Based on the characteristics of complex social networks in the real world,the model is extended to heterogeneous networks to model and analyze the rumor propagation process on heterogeneous networks.The dynamics of rumor propagation is simulated in BA scale-free network,Facebook network and other social networks,and the influence of three factors on rumor propagation is investigated.The research shows that whether on homogeneous network or heterogeneous network,the neutral attitude of the crowd towards rumors will reduce the speed of rumor spreading and the final rumor size.Due to the frequent information exchange in complex social networks,remembering mechanism plays a more major role on rumor spreading process than forgetting mechanism.Therefore,when forgetting and memory mechanisms are considered,the forgetting rate and remembering rate have an influence on final rumor size.The topological characteristics of the real-world social networks are analyzed.Simulations of the rumor diffusion process on these networks are conducted,which is in line with the reality.(3)Analysis of immunization strategies on homogeneous networks and heterogeneous networks.The effectiveness of random immunization strategy is analyzed on homogeneous network.The result shows that the peak density of infected individuals decrease with the increase of random immunization ratio,which means the random immunization strategy is effective.The effectiveness of random immunization and target immunization strategies is analyzed on heterogeneous network,and the threshold of immunization is derived.The results of simulation show that target immunization is more effective than random immunization at the same average immunization ratio.