Key nodes mining for complex networks based on local gravity model

Abstract

Identification of key nodes in complex networks can effectively speed up the spread of favourable information or prevent the spread of rumours and diseases. An algorithm based on local gravity model is proposed to mine the key spreaders in complex networks. The existing algorithms based on gravity model consider the shortest distance between nodes. However, nodes not only influence each other through the shortest path, which will lead the loss of information between nodes. Different from the existing gravity model, the distance considered in this model is not the shortest distance between nodes, but the reciprocal of the number of feasible paths between nodes. Conveniently, the model is called FPLGM (Local Gravity Model Based on Feasible Paths). Ten different networks are utilised to verify the effectiveness of FPLGM. Results show that the FPLGM performs best in comparison with the well-known state-of-the-art methods.

KEYWORDS:

• Complex networks
• key nodes mining
• local gravity model

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by National Natural Science Foundation of China [grant number 62276058, 61902057, 41774063]; Fundamental Research Funds for the Central Universities [grant number N2217003]; Joint Fund of Science & Technology Department of Liaoning Province and State Key Laboratory of Robotics, China [grant number 2020-KF-12-11].

Notes on contributors

Tao Ren

Tao Ren received the BS degree in automatic control and the MS and PhD degrees in control theory and control engineering from Northeastern University, Shenyang, China, in 2003, 2005 and 2007, respectively. He is currently a Professor with Northeastern University. He is in charge of 14 projects, such as the National Natural Science Foundation of China, and so on. He has published more than 30 high-qualified academic articles in several high-ranking journals or conferences. His current research interests include complex networks and intelligent optimisation algorithm. He has received the Chinese People’s Liberation Army Science and Technology Progress Award and several other academic awards.

Shixiang Sun

Shixiang Sun received the BS and MS degrees from the School of Mathematics and Statistics Science, Ludong University, Yantai, China, in 2014 and 2018, respectively. She is currently a Doctor with Northeastern University. She has published five qualified academic articles in high-ranking journals or conferences. Her current research interests include intelligent optimisation algorithm, complex networks and stochastic control.

Yanjie Xu

Yanjie Xu received the BS degree in software engineering from Nanchang University, Nanchang, China, in 2015. She is currently pursuing the PhD degree in software engineering with Northeastern University, Shenyang, China. Her current research interests include complex networks and machine learning.

Georgi Marko Dimirovski

Georgi Marko Dimirovski is a Research Professor (life-time) of Automation & Systems Engineering at the Faculty of Electrical-Electronics Engineering and Information Technologies of SS Cyril and Methodius University of Skopje, R. Macedonia, and a Professor of Computer Science & Information Technologies at the Faculty of Engineering of Dogus University of Istanbul as well as an Invited Professor of Computer & Control Sciences at the Graduate Institutes of Istanbul Technical University, R. Turkey, and a ‘Pro Universitas’ Professor at the Doctoral School of Obuda University in Budapest, Hungary. He is a Foreign Member of Serbian Academy of Engineering Sciences in Belgrade. He received his Dipl.-Ing. degree in 1966 from SS Cyril and Methodius University of Skopje, Macedonia, MSc degree in 1974 from University of Belgrade, R. Serbia, and PhD degree in 1977 from University of Bradford, England, UK. He got his postdoctoral position in 1979 and subsequently was a Visiting Research Professor at the University of Bradford in 1984, 1986 and 1988 as well as at the University of Wolverhampton in 1990 and 1991. He was a Senior Research Fellow and Visiting Professor at Free University in Brussels, Belgium, in 1994 and also at Johannes Kepler University in Linz, Austria, in 2000. His research interests include nonlinear systems and control, complex dynamical networks, switched systems, and applied computational intelligence to decision and control systems. Currently, as an associate editor, he serves Journal of the Franklin Institute, Asian J. of Control and Intl. J. of Automation & Computing.