Evaluating The Importance Of Nodes In Social Networks Based On Topology Potential

Social network is a kind of complex network.Along with the rapid development of Internet,the communication between people is more and more closely,the dissemination of the information is faster and faster.The social network which is formed on this,not only the relation becomes more complex,the unstable factors in the network will become hard to control.Individuals or organizations are in the social network,changes of the network's structure will be related to everyone's benefit,it will affect most people.How to control the unstable factors in the network? To find the important nodes through the network's topology structure is a good way.By the controlling of the important nodes,the necessary monitoring and management will grasp the whole social network's structure.Most previous analyses of the social network are carried out in a simple graph,and the importance of the nodes is usually based on the node degree,centrality or betweenness.Ignoring the intrinsic characteristics of the node and the relationship between the nodes will cause the inaccurate results of the analysis.This paper will establish the hypergraph model of the social network,analyze the importance of the nodes in the hypergraph model.First of all,some improvements will be done to the hypergraph model of the social network.The inherent property of the nodes and the links between the nodes is used into the evaluation process.Secondly,get the topology potential value of the node based on the cognitive data field theory in physics.In the calculation of the node quality used the entropy-weight method,rule out other methods obtain the human interference factors of node quality.In the calculation of the shortest path in this paper presents the Dijkstra algorithm based on hypergraph.Thirdly,present a algorithm of replacing to get the order of the node's importance by improving the algorithm of deleting.Then,through the node's importance ranking and based on the feature that the nodes in the data field to attract each other to form a community,present a method to find the hypergraph model of the social network's community detection to prove the validity and the usability of the evaluation results.Finally,verify the above proposed theory according to the experiment.