Comparing journals from different fields of Science and Social Science through a JCR Subject Categories Normalized Impact Factor
Pablo Dorta-Gonzalez, Maria Isabel Dorta-Gonzalez

TL;DR
This paper introduces a normalization method for Impact Factors across disciplines using principal component analysis and category-based adjustments, reducing ranking disparities among journals in Science and Social Science.
Contribution
It proposes the Categories Normalized Impact Factor (CNIF), a new metric that accounts for disciplinary differences, improving comparability of journal impact across fields.
Findings
Principal components explain over 78% of variance in impact factors.
CNIF reduces ranking gaps by approximately 32%.
Publication and citation behaviors are not the main factors in impact factor variance.
Abstract
The journal Impact Factor (IF) is not comparable among fields of Science and Social Science because of systematic differences in publication and citation behaviour across disciplines. In this work, a decomposing of the field aggregate impact factor into five normally distributed variables is presented. Considering these factors, a Principal Component Analysis is employed to find the sources of the variance in the JCR subject categories of Science and Social Science. Although publication and citation behaviour differs largely across disciplines, principal components explain more than 78% of the total variance and the average number of references per paper is not the primary factor explaining the variance in impact factors across categories. The Categories Normalized Impact Factor (CNIF) based on the JCR subject category list is proposed and compared with the IF. This normalization is…
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