Testing for universality of Mendeley readership distributions

TL;DR

This study investigates whether Mendeley readership distributions are universal across scientific fields, finding that they share similar shapes and can be rescaled to a common form, with some limitations on the extreme values.

Contribution

It is the first to test the universality of Mendeley readership distributions across fields, extending methods used for citation distributions.

Findings

Readership distributions are similar across fields.

Rescaling can unify distributions except for extreme values.

Field-specific distributions collapse well after rescaling.

Abstract

Altmetrics promise useful support for assessing the impact of scientific works, including beyond the scholarly community and with very limited citation windows. Unfortunately, altmetrics scores are currently available only for recent articles and cannot be used as covariates in predicting long term impact of publications. However, the study of their statistical properties is a subject of evident interest to scientometricians. Applying the same approaches used in the literature to assess the universality of citation distributions, the intention here is to test whether the universal distribution also holds for Mendeley readerships. Results of the analysis carried out on a sample of publications randomly extracted from the Web of Science confirm that readerships seem to share similar shapes across fields and can be rescaled to a common and universal form. Such rescaling results as not particularly effective on the right tails. In other regions, rescaling causes a good collapse of field specific distributions, even for very recent publications.