| With the rapid development of the Internet,the research on the influence of social network nodes has become a hot topic.Influence analysis is of great significance to understand the network rumors,information,and virus transmission and so on.Most of the current studies focus on how to evaluate and measure the influence,and there are few mechanisms which study the influence from the perspective of individual to group.In this paper,the influence is regarded as the flow of information in the network.Based on this idea,this paper proposes an algorithm of individual influence on the group based on the betweenness Centrality and the contribution of nodes,and simulates and verifies it.Finally,the visualization platform of complex network data is constructed in this paper.The results are as follows:1,This paper summarizes the status of research on node influence at home and abroad,introduces some classical algorithms to measure the importance of nodes,and analyzes the limitations of the algorithms based on topology,user behavior,and topic and so on.The theoretical basis of complex network is introduced in detail,including graph,important node algorithm and virus propagation model.2,According to the current research situation,an individual to group influence algorithm is proposed to describe the impact contribution of nodes to the whole network.The simulation results of the algorithm in different networks are verified,and the quantitative analysis of the algorithm results is carried out,and the distribution of individual influence on the population is summarized.3,The data visualization platform based on web is constructed.Firstly,it analyzes the current research situation of network data visualization,the development environment,and the related technologies to analyze the requirements at the same time.Then make the technical route and the system structure and carry on each module design to the platform;finally complete the platform to carry on the test... |
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