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Issue:Quantifying individual scientific output in terms of a new intuitionistic fuzzy sets based author-level metrics (IFALM)

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Title of paper: Quantifying individual scientific output in terms of a new intuitionistic fuzzy sets based author-level metrics (IFALM)
Author(s):
Vassia Atanassova
Bioinformatics and Mathematical Modelling Department, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, 105 Acad. Georgi Bonchev Str., Sofia 1113, Bulgaria
vassia.atanassova@gmail.com
Presented at: 25th ICIFS, Sofia, 9—10 September 2022
Published in: Notes on Intuitionistic Fuzzy Sets, Volume 28 (2022), Number 3, pages 319–333
DOI: https://doi.org/10.7546/nifs.2022.28.3.319-333
Download:  PDF (937  Kb, Info)
Abstract: The present paper proposes the idea of formulating a new author-level citation metrics, quantifying the individual’s scientific output, which uses the concept of intuitionistic fuzzy sets. This new metrics gives more visibility to the proportion of direct self-citations and hidden (co-author or collaborative) self-citations in the form of an intuitionistic fuzzy pair. Examples are given retrieving the necessary information from Scopus, one of the largest databases of peer-reviewed literature, which algorithmically enables retrieval of one’s citations including and excluding their own or their co-authors’ self-citations, as well as the calculation of three different values of one’s h-index with and without these respectively. Linear and triangular graphical representations are given, as well as comparisons with the concept proposed in 2005 by Jorge E. Hirsch, the now famous h-index, and ideas for future elaboration of the concept of the new intuitionistic fuzzy sets based author-level metrics, or shortly IFALM.
Keywords: Intuitionistic fuzzy sets, Intuitionistic fuzzy pairs, Bibliometrics, Citations, Self-citation, Scopus, H-index.
AMS Classification: 03E72.
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