Algorithmic procedure for finding semantically related journals
Journal of the American Society for Information Science and Technology
Making an equality of ISI impact factors for different subject fields: Research Article
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Modifying the journal impact factor by fractional citation weighting: The audience factor
Journal of the American Society for Information Science and Technology
Differences in impact factor across fields and over time
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Garfield and the impact factor
Annual Review of Information Science and Technology
Conference paper selectivity and impact
Communications of the ACM
Relative status of journal and conference publications in computer science
Communications of the ACM
The relation between Eigenfactor, audience factor, and influence weight
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
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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 Journal Citation Reports (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 based on the JCR subject category list is proposed and compared with the IF. This normalization is achieved by considering all the indexing categories of each journal. An empirical application, with one hundred journals in two or more subject categories of economics and business, shows that the gap between rankings is reduced around 32 % in the journals analyzed. This gap is obtained as the maximum distance among the ranking percentiles from all categories where each journal is included.