The Model Research And Analysis System Realization Of Social Network Node Influence Measurement

The rapid development of modern science and technology makes each resident more closely connected,thus making the social relationship between people more complex.Social influence,as an ability to change the thoughts or behaviors of others,has been the object of analysis in sociology,communication,dynamics and other fields.From the perspective of social network,the complex social relations are quantified as nodes and edges,and then the influence of nodes in social network can be measured and analyzed.In practical application,the measurement of social network node influence is of great significance to the research of policy implementation,public opinion monitoring,network marketing,prevention and control of infectious diseases and so on.As a result of the nodes in the network heterogeneity,makes the different location of the node for the entire network influence other nodes,thus to the overall form of the network and maintaining has different role and influence.In this paper,the status and role of nodes in different positions in the network are studied and analyzed,and a Web system is built to implement the measurement model.In addition,visual analysis and interaction of the network as well as the compilation of notes are also added,so as to provide a reference and learning space for researchers interested in social influence.The main contributions of this paper are as follows:1.This paper studies the theory of influence measurement.Through the research on ternary closures and structural holes in sociology,the influence measurement method of complex network nodes,and the partition community,this paper analyzes the small network data sets,and proposes the DCCK(Degree Constraint Community k-shell)calculation model of the hybrid embeddability measurement model and structural hole measurement model for nodes in different locations.Combining SIR propagation model and Kendall rank correlation coefficient,the real social network data is analyzed and verified.2.Based on the process of software engineering,this paper analyzes and expounds the system from four aspects:demand analysis,design,implementation and test.Combining Vue front-end and Django back-end framework,the design and implementation of the system are carried out in the way of front and rear end separation.The system mainly provides users with a variety of functions such as network data management,network data calculation,data visualization,note-taking service,etc.Users can select network data to calculate node influence,and conduct visual interaction through the front page,and can also edit and share learning notes online.