Improved Elastic Model Based on K-shell Algorithm Identifies Key Nodes in Complex Networks
Jing He, Xiumei Wei, Xuesong Jiang · 2023
Identifying key nodes in complex networks is an effective way to improve network robustness. And it is also conducive to a more comprehensive and profound understanding of different networks and their characteristics. Identifying key nodes in complex networks has become a hot issue in academic circles. And the methods of mining key nodes in complex networks are increasingly diversified. Inspired by the elastic model, this paper proposes an improved spring centrality (KSSC) based on k-shell algorithm. KSSC aims to identify the key nodes in complex networks quickly and accurately. This method takes advantage of the characteristic of k-shell algorithm. It uses the value of node ks to represent the position of node in the whole complex network, too. At the same time, a position coefficient is proposed. The value of this coefficient can transform the model between the improved elastic model and the traditional elastic model. Then the node influence can be calculated by combining the position information with the elastic model. In order to prove the practical significance of this method, the improved elastic model is applied to the social networks. Compared with other algorithms, the experimental results obtained by repeated experiments show that KSSC has higher accuracy in the identification of key nodes.