Identifying influential nodes in complex networks based on AHP

Tian Bian, Jiantao Hu and Yong Deng

Physica A: Statistical Mechanics and its Applications, 2017, vol. 479, issue C, 422-436

Abstract: In the field of complex networks, how to identify influential nodes in the network is still an important research topic. In this paper, a method to identify the influence of the node based on Analytic Hierarchy Process (AHP) is proposed. AHP, as a multiple attribute decision making (MADM) technique has become an important branch of decision making since then. Every centrality measure has its own disadvantages and limitations, thus we consider several different centrality measures as the multi-attribute of complex network in AHP application. AHP is used to aggregate the multi-attribute to obtain the evaluation of the influence of each node. The experiments on four real networks and an informative network show the efficiency and practicability of the proposed method.

Keywords: Complex networks; Influential nodes; AHP; MADM; Centrality measure (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:479:y:2017:i:c:p:422-436

DOI: 10.1016/j.physa.2017.02.085

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