Scopus's Source Normalized Impact per Paper (SNIP) versus a Journal Impact Factor based on Fractional Counting of Citations

TL;DR

This paper compares the SNIP indicator and traditional impact factors, proposing fractional citation counting to normalize impact measures across fields and enable significance testing of differences.

Contribution

It introduces fractional counting of citations to normalize impact measures and allows significance testing, addressing limitations of existing impact indicators.

Findings

SNIP normalization decisions prevent significance testing

Fractional counting contextualizes impact at the paper level

Impact differences between journals can be statistically tested

Abstract

Impact factors (and similar measures such as the Scimago Journal Rankings) suffer from two problems: (i) citation behavior varies among fields of science and therefore leads to systematic differences, and (ii) there are no statistics to inform us whether differences are significant. The recently introduced SNIP indicator of Scopus tries to remedy the first of these two problems, but a number of normalization decisions are involved which makes it impossible to test for significance. Using fractional counting of citations-based on the assumption that impact is proportionate to the number of references in the citing documents-citations can be contextualized at the paper level and aggregated impacts of sets can be tested for their significance. It can be shown that the weighted impact of Annals of Mathematics (0.247) is not so much lower than that of Molecular Cell (0.386) despite a five-fold difference between their impact factors (2.793 and 13.156, respectively).