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Semi-global triangular centrality measure for identifying the influential spreaders from undirected complex networks

Namtirtha, A and Dutta, B and Dutta, A (2022) Semi-global triangular centrality measure for identifying the influential spreaders from undirected complex networks. In: Expert Systems with Applications, 206 .

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Official URL: https://doi.org/10.1016/j.eswa.2022.117791


The influential spreaders play a significant role in maximizing or controlling any spreading process in a network. In the literature, many methods have been proposed to identify influential spreaders. In this article, we classify all the methods mainly into four categories, such as local centrality, global centrality, semi-global centrality and hybrid centrality. Among them, we have found semi-global centrality based methods have immense potential in identifying the influential spreaders from various types of network structures. However, we have observed that the existing semi-global centrality methods can identify the spreaders from the periphery of a network, where the nodes in the periphery are loosely coupled and the collective influence in the peripheral region of a spreading process will be nominal. We propose a new indexing method “semi-global triangular centrality”, which does not consider the best spreaders from the periphery. The proposed method maximizes the total collective influence of a spreading process by selecting the best spreaders from the dense part of a network. We have examined the performance of the proposed method using the Susceptible–Infected–Recovered epidemic model and applied to nine real-networks. The experimental result reveals that the proposed method performs better than the other centrality methods in terms of spreading dynamics.

Item Type: Journal Article
Publication: Expert Systems with Applications
Publisher: Elsevier Ltd
Additional Information: The copyright for this article belongs to the Elsevier Ltd.
Keywords: Epidemiology; Spreaders, Centrality measures; Global centrality; Influential spreader; Local centralities; Loosely coupled; Network structures; Semi-global; Semi-global triangular centrality; SIR epidemic model; Spreading abilities, Complex networks
Department/Centre: Division of Interdisciplinary Sciences > Computational and Data Sciences
Date Deposited: 14 Jul 2022 09:16
Last Modified: 14 Jul 2022 09:16
URI: https://eprints.iisc.ac.in/id/eprint/74402

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