MINE: Identifying Top- k Vital Nodes in Complex Networks via Maximum Influential Neighbors Expansion

Xinyu Huang, Dongming Chen, Dongqi Wang and Tao Ren
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Xinyu Huang: Software College, Northeastern University, Shenyang 110169, China
Dongming Chen: Software College, Northeastern University, Shenyang 110169, China
Dongqi Wang: Software College, Northeastern University, Shenyang 110169, China
Tao Ren: Software College, Northeastern University, Shenyang 110169, China

Mathematics, 2020, vol. 8, issue 9, 1-25

Abstract: Identifying vital nodes in complex networks is of paramount importance in understanding and controlling the spreading dynamics. Currently, this study is facing great challenges in dealing with big data in many real-life applications. With the deepening of the research, scholars began to realize that the analysis on traditional graph model is insufficient because many nodes in a multilayer network share connections among different layers. To address this problem both efficiently and effectively, a novel algorithm for identifying vital nodes in both monolayer and multilayer networks is proposed in this paper. Firstly, a node influence measure is employed to determine the initial leader of a local community. Subsequently, the community structures are revealed via the Maximum Influential Neighbors Expansion (MINE) strategy. Afterward, the communities are regarded as super-nodes for an iteratively folding process till convergence, in order to identify influencers hierarchically. Numerical experiments on 32 real-world datasets are conducted to verify the performance of the proposed algorithm, which shows superiority to the competitors. Furthermore, we apply the proposed algorithm in the graph of adjacencies derived from the maps of China and USA. The comparison and analysis of the identified provinces (or states) suggest that the proposed algorithm is feasible and reasonable on real-life applications.

Keywords: complex network; multilayer networks; node ranking; influence maximization (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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