Testing for universality of Mendeley readership distributions
| Autor: | Ciriaco Andrea D'Angelo, Samuele Di Russo |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
Altmetrics Universal distribution Computer science 05 social sciences Computer Science - Digital Libraries Library and Information Sciences Settore ING-IND/35 - Ingegneria Economico-Gestionale 050905 science studies Computer Science Applications Universality (dynamical systems) Audience measurement Impact Bibliometrics Econometrics CSS Mendeley readership Digital Libraries (cs.DL) 0509 other social sciences 050904 information & library sciences Citation |
| Zdroj: | Journal of informetrics 13 (2019): 726–737. doi:10.1016/j.joi.2019.03.011 info:cnr-pdr/source/autori:D'Angelo, Ciriaco Andrea; Di Russo, Samuele/titolo:Testing for universality of Mendeley readership distributions/doi:10.1016%2Fj.joi.2019.03.011/rivista:Journal of informetrics (Print)/anno:2019/pagina_da:726/pagina_a:737/intervallo_pagine:726–737/volume:13 |
| ISSN: | 1751-1577 |
| DOI: | 10.1016/j.joi.2019.03.011 |
| Popis: | 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. (C) 2019 Elsevier Ltd. All rights reserved. |
| Databáze: | OpenAIRE |
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