Research On Sequence Of The Node Importance In Social Network Based On The Von Neumann Entropy

With the continuous development of the Internet.Complex network applications can be seen everywhere in our life.In real life,many complex systems can be modeled as a complex network for analysis.While the social network is a kind of common complex network.It is not only a way to present the data of our real life,but also a way to study the characteristics of complex network's data.The complex network is growing more and more important,especially for the study of social networks.Although the Internet brings a lot of convenience,but there is also a problem of network security,hackers will swoop and attack the important nodes in the network,so that the whole network cannot work normally or in a state of paralysis.Therefore,it is very important to study the importance ranking of nodes in complex networks.Different networks often have different forms of topological structure and physical structure,according to the specific characteristics of complex networks and the relationship between the nodes,the network will have diverse strategies.Therefore,how to evaluate the status of nodes in the network more accurately and effectively is an urgent problem to solve.In this paper,the main works are as follows:(1)In view of the problem of incomplete sorting factors which cause by the traditional sort algorithm,leading to the result of sorting is inaccurate.This paper presents a single node sort algorithm which is based on von Neumann entropy.This algorithm uses the eigenvector value factor and compared with other classical algorithms,this algorithm mainly through deleting nodes one by one to calculate the entropy change.Lastly obtaining a single node importance of this network.Experiments show that the algorithm can reflect more accurately the status of a single node in the network.(2)In the process of algorithm implementation,the experimental results show that a network also has an important node of a module(core),but sometimes is not just a node,the interaction between the nodes will have an impact on the importance of node scheduling,thus using the classical experimental data set dolphin data and karate club network,thus positive action that is often produced between the importance of single node is verified,whereas it is the negative effect.(3)This paper puts forward an improved algorithm which is based on the von Neumann and in the previous chapter sand the thought of "weight" between nodes,in the actual network function is not the same,i.e.each edge is given weight function,given different treatment.This study is the power function in the process of the experiment by adjusting the power broken value experiments show that the algorithm improved the flexibility and effectiveness.