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On the normalization and distributional adjustment of journal ranking metrics: A simple parametric approach
Author(s) -
Ryan Haley M.
Publication year - 2017
Publication title -
journal of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.903
H-Index - 145
eISSN - 2330-1643
pISSN - 2330-1635
DOI - 10.1002/asi.23663
Subject(s) - normalization (sociology) , journal ranking , computer science , ranking (information retrieval) , citation , impact factor , metric (unit) , simple (philosophy) , parametric statistics , citation analysis , nonparametric statistics , rank (graph theory) , econometrics , statistics , data mining , information retrieval , mathematics , library science , social science , engineering , sociology , political science , operations management , philosophy , epistemology , combinatorics , law
This paper presents a simple parametric statistical approach to comparing different citation‐based journal ranking metrics within a single academic field. The mechanism can also be used to compare the same metric across different academic fields. The mechanism operates by selecting an optimal normalization factor and an optimal distributional adjustment for the rank–score curve, both of which are instrumental in making sound intermetric and interfield journal comparisons.