Abstract
We used the Journal Impact Factor (JIF) to develop the hjif-index, calculated in a similar way to h-like indices. To this end, we mapped the JIFs of one JCR group to natural numbers, and evaluated the degree of correspondence between the interval from zero to the highest JIF in the group and a set of natural numbers. Next, we plotted the straight line y = x to obtain the group’s hjif-index as the JIF corresponding to the journal immediately above the straight line. We call the set of journals above the straight line the hjif-core. We calculated hjif-indices corresponding to the 2-year JIF (hjif2-index) and 5-year JIF (hjif5-index) windows for all 176 JCR groups listed in the 2014 Science edition. We also studied derived indicators such as the distribution of journals in JCR groups according to their hjif-indices, the distribution of journals and JIFs in the hjif-core, and other variables and indicators. We found that the hjif2- and hjif5-index behaved in a similar way, and that in general their distribution showed a peak followed by a relatively long tail. The hjif-index can be used as a tool to rank journals in a manner that better reflects the variable number of journals within a given JCR group and in each group’s hjif-core as an alternative to the more arbitrary JCR-based percentile ranking.
Highlights
Introduction and ObjectivesWe used the Journal Impact Factor (JIF) to develop the hjif-index, calculated in a similar way to h-like indices
We found that the hjif2- and hjif5-index behaved in a similar way, and that in general their distribution showed a peak followed by a relatively long tail
The hjif-index can be used as a tool to rank journals in a manner that better reflects the variable number of journals within a given JCR group and in each group’s hjif-core as an alternative to the more arbitrary JCR-based percentile ranking
Summary
We used the Journal Impact Factor (JIF) to develop the hjif-index, calculated in a similar way to h-like indices In this Introduction we summarize the usual definition and interpretation of the h-index, describe some of the many variants of the h-index, and focus in the problem of h-like indicators defined with non-natural numbers. Of all articles published by a given author, N − h indicates those that have received fewer than h citations each [1,2] This index is often assumed to combine “quantity” (number of publications) and “quality” (citations) factors. To increase ones h-index, a scientist should produce as many articles as possible, and as many different publications should be cited as many times as possible. This popular index is used as an indicator by both Scopus and Web of Science
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