Abstract
It is very important to identify the important nodes in the network. On the basis of K-shell algorithm, this study studied the recognition of important nodes in complex networks. Firstly, this study introduced concepts of edge weight and influence coefficient, designed an IKS algorithm, and analyzed its recognition effect in Zachary network and real micro blog network. It was found from the experimental results that the partition results of the K-shell algorithm were coarse, while the partition results of the IKS algorithm were refined; the IKS algorithm could sort the important nodes accurately on the basis of the K-shell algorithm, and its rationality was higher than that of closeness centralization and PaperRank algorithm. The partition results in microblog network also verified the effectiveness of the improved method. The experimental results show that the IKS algorithm is reliable in the important node identification, which makes some contributions to the recognition of important nodes in complex network.
Highlights
Because of constant societal developments, people’s daily activities are progressively closely linked
The classical K-shell algorithm was improved and an improved K-shell (IKS) algorithm was designed for identifying the important nodes
Compared with K-shell algorithm, IKS had a more precise recognition of important nodes, and the number of the top 10 important nodes was 1, which showed that IKS algorithm had strong recognition ability. It showed that the IKS algorithm made up for the defect of the rough division of the classic K-shell algorithm and could effectively sort the important nodes
Summary
Because of constant societal developments, people’s daily activities are progressively closely linked. The important nodes in the network community are the nodes that have an important impact on the network, which has very important practical significance for controlling rumor spread, the spread of infectious diseases [2], traffic conditions [3], etc. This is why the recognition algorithm of important nodes has been widely researched. Experiments on the Zachary and the Weibo networks verified the reliability of the method, which is conducive to effectively measuring the important nodes in complex networks and can be used in controlling the spread of infectious diseases and rumors
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
