Evolution And Prediction Of Propagation-driven Networks

Complex network research has become an important interdisciplinary subject,covering many fields,such as sociology,physics,computer science and so on.Link prediction and information propagation are two indispensable aspects in this field,and their interaction provides important insights for understanding and applying complex networks.In the evolution of network structure,the link prediction method can predict the future links in the network and reveal the evolution of the internal structure of the network.The main work of this thesis is as follows.(1)Build a link prediction algorithm by analyzing the cooperation characteristics of scientists’ cooperation network to predict the possible cooperation between scientists.Firstly,a simulated network is abstracted by analyzing the structure and node attributes of the real network.Secondly,by improving the SIS infectious disease propagation model,the process of information propagation in the cooperative network is simulated.In view of the influence of information propagation on the network,the link prediction algorithm is improved.Finally,the experimental results in the scientist cooperation network show that the hybrid weighted link prediction algorithm combining node attributes and propagation factors can improve the accuracy of link prediction and provide suggestions for scientists to find partners.By comparing the simulation network with the real network,the validity of the propagation model in the scientist cooperation network and the accuracy of the hybrid weighted link prediction algorithm are verified.(2)The link prediction algorithm is used to obtain the similar values between nodes,so as to construct the information propagation model that conforms to the propagation characteristics of different topics,and then analyze the propagation of different topics.Through the screening and processing of multiplex network data,a weighted multiplex social network in line with the social reality is constructed,and different categories of microblog forwarding are simulated.Weighted link prediction index based on inter-layer correlation is designed,and a relative optimal similarity algorithm for node pair in the weighted multiplex social network is found.And simulated the spread of different kinds of messages in the social network,so as to analyze the structure of the social network and the propagation characteristics.In this study,we consider the interlayer information and weighted information of the multiplex network,and try to construct a propagation model according to the different propagation phenomena of each layer network,so as to simulate the propagation of information.This chapter analyzes and discusses the influence of different factors on the experimental results,and observes the dynamic characteristics of the multiplex network propagation model and the classical propagation model.Through the analysis and prediction of the data obtained by these algorithms,human beings will have a more comprehensive and profound understanding of the law of network propagation in the real world.(3)Construct a propagation-weighted network through information propagation in the network to study the influence of information propagation on the network structure.Dynamic propagation will affect the change of network structure.The iterative propagation of information in the network changes the connection strength of chain edges between nodes.In the process of information iterative propagation in the network,it becomes the research focus of this chapter to concretize the network structure changes influenced by the characteristics of propagation dynamics.The emergence of chain edge is the micro change of network structure,while the division of community is the macro change of network structure.Based on this,the concept of node participation is proposed to quantify the influence of different users on the information propagation in the network.Through the analysis of the iterative propagation of information,the weight network of different networks based on the iterative propagation of information is constructed.Finally,the chain edge and community division in the network are analyzed to achieve the purpose of quantifying the influence of network propagation on network structure.