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An EigenFactor-weighted power mean generalization of the Euclidean Index
- Source :
- PLoS ONE, Vol 14, Iss 2, p e0212760 (2019), PLoS ONE
- Publication Year :
- 2019
- Publisher :
- Public Library of Science (PLoS), 2019.
-
Abstract
- 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.
- Subjects :
- Percentile
Index (economics)
Research Facilities
Generalization
Physiology
Science
Libraries
Social Sciences
050905 science studies
Research and Analysis Methods
Information Centers
Education
Creativity
Sociology
Citation analysis
Statistics
Euclidean geometry
Medicine and Health Sciences
Psychology
Obesity
Educational Attainment
Mathematics
Scientific Publishing
Multidisciplinary
05 social sciences
Body Weight
Cognitive Psychology
Biology and Life Sciences
Eigenfactor
Research Assessment
Weighting
Physiological Parameters
Bibliometrics
Citation Analysis
Cognitive Science
Medicine
0509 other social sciences
Journal Impact Factor
Periodicals as Topic
050904 information & library sciences
Citation
Research Article
Neuroscience
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 14
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....c5f9ea0a8d87812368b6122041410d63