Identification of influential users in social network using gray wolf optimization algorithm

A challenging issue in viral marketing is to effectively identify a set of influential users. By sending the advertising messages to this set, one can reach out the largest area of the network. In this paper, we formulate the influence maximization problem as an optimization problem with cost functi...

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Bibliographic Details
Published in:Expert systems with applications 2020-03, Vol.142, p.112971, Article 112971
Main Authors: Zareie, Ahmad, Sheikhahmadi, Amir, Jalili, Mahdi
Format: Article
Language:English
Subjects:
Algorithms
Computing time
Cost function
Gray wolf optimizer
Heuristic methods
Influence maximization
Maximization
Nodes
Optimization
Optimization algorithms
Social networks
Spreading process
Viral marketing
Wolves
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Summary:A challenging issue in viral marketing is to effectively identify a set of influential users. By sending the advertising messages to this set, one can reach out the largest area of the network. In this paper, we formulate the influence maximization problem as an optimization problem with cost functions as the influentiality of the nodes and the distance between them. Maximizing the distance between the seed nodes guarantees reaching to different parts of the network. We use gray wolf optimization algorithm to solve the problem. Our experimental results on three real-world networks show that proposed method outperforms state-of-the-art influence maximization algorithms. Furthermore, it has lower computational time than other meta-heuristic methods.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2019.112971