The effect on citation inequality of differences in citation practices at the Web of Sciences subject category level

This paper studies the impact of differences in citation practices at the sub-field, or Web of Science subject category level using the model introduced in Crespo et al. (2012) according to which the number of citations received by an article depends on its underlying scientific influence and the field to which it belongs. We use the same Thomson Reuters dataset of about 4.4 million articles published in 1998-2003 with a fiveyear citation window used in Crespo et al. (2013) to analyze a classification system consisting of 22 broad fields. The main results are the following four. Firstly, as expected, when the classification system goes from 22 broad fields to 219 sub-fields the effect on citation inequality of differences in citation practices increases from approximately 14% at the field level to 18% at the sub-field level. Secondly, we estimate a set of exchange rates (ERs) to express the citation counts of articles in a wide quantile interval into the equivalent counts in the all-sciences case. For example, in the fractional case we find that in 187 out of 219 sub-fields the ERs are reliable in the sense that the coefficient of variation is smaller than or equal to 0.10. ERs are estimated over the [660, 978] interval that, on average, covers about 62% of all citations. Thirdly, in the fractional case the normalization of the raw data using the ERs (or sub-field mean citations) as normalization factors reduces the importance of the differences in citation practices from 18% to 3.8% (3.4%) of overall citation inequality. Fourthly, the results in the fractional case are essentially replicated when we adopt the multiplicative approach