Paper Info
Title
Finding Influential Nodes in Multiplex Networks Using a Memetic Algorithm
Abstract
In order to find the nodes with better propagation ability, a large body of studies on the influence maximization problem has been conducted. Several influence spreading models and corresponding optimization algorithms have been proposed and successfully identified the infusive seeds in single isolated networks. However, as indicated by some recent studies and online materials, modern networked systems tend to have more complicated structures and multiple layers, which makes it difficult for existing seed determination techniques to deal with these networks. Thus, finding influential nodes in realistic multiplex networks remains open. Therefore, this paper aims to design an extended influence spreading model to simulate the influence diffusion process in multiplex networks, based on which a memetic algorithm is developed to find the seeds that are influential in all network layers. Experimental results on synthetic and real-world networks validate the effectiveness of the proposed algorithm. These results are helpful for identifying potential propagators in multiplex social networks, and provide solutions to analyze and gain deeper insights into networked systems.
Year
DOI
Venue
2021
10.1109/TCYB.2019.2917059
IEEE Transactions on Cybernetics
Keywords
DocType
Volume
Influence maximization,multiplex networks,optimization
Journal
51
Issue
ISSN
Citations 
2
2168-2267
4
PageRank 
References 
Authors
0.37
0
3
Name
Order
Citations
PageRank
Shuai Wang1112.18
Jing Liu21043115.54
Yaochu Jin36457330.45