Convex combinations of centrality measures

Keng, Ying Ying and Kwa, Kiam Heong and McClain, Christopher (2021) Convex combinations of centrality measures. Journal of Mathematical Sociology, 45 (4). pp. 195-222. ISSN 0022-250X, DOI

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Despite a plethora of centrality measures were proposed, there is no consensus on what centrality is exactly due to the shortcomings each measure has. In this manuscript, we propose to combine centrality measures pertinent to a network by forming their convex combinations. We found that some combinations, induced by regular points, split the nodes into the largest number of classes by their rankings. Moreover, regular points are found with probability 1 and their induced rankings are insensitive to small variation. By contrast, combinations induced by critical points are scarce, but their presence enables the variation in node rankings. We also discuss how optimum combinations could be chosen, while proving various properties of the convex combinations of centrality measures.

Item Type: Article
Funders: Faculty of Science University of Malaya Research Grant (RF008B-2018)
Uncontrolled Keywords: Centrality measures; Convex combinations; Regular points
Subjects: H Social Sciences > HM Sociology
Q Science > QA Mathematics
Divisions: Faculty of Science > Institute of Mathematical Sciences
Depositing User: Ms Zaharah Ramly
Date Deposited: 08 Apr 2022 07:02
Last Modified: 08 Apr 2022 07:02

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