
An EigenFactor-weighted power mean generalization of the Euclidean Index
Author(s) -
M. Ryan Haley
Publication year - 2019
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0212760
Subject(s) - vetting , generalization , weighting , percentile , index (typography) , flexibility (engineering) , euclidean geometry , computer science , mathematics , statistics , citation , econometrics , medicine , library science , mathematical analysis , geometry , computer security , world wide web , radiology
This paper proposes a weighted generalization of the recently developed Euclidean Index. The weighting mechanism is designed to reflect the reputation of the journal within which an article appears. The weights are constructed using the Eigenfactor Article Influence percentiles scores. The rationale for assigning weights is that citations in more prestigious journals should be adjusted to logically reflect higher costs of production and higher vetting standards, and to partially counter several pragmatic issues surrounding truncated citation counts. Simulated and empirical demonstrations of the proposed approaches are included, which emphasize the flexibility and efficacy of the proposed generalization.