Casey, Arlene J, Ahmadi,Samad and Murtagh, Fionn - Archives of Data Science, Series A

Article Details

Title Exploring Relationships between Article Level Metrics and Content Quantities in Academic Papers
Authors Casey, Arlene J, Ahmadi,Samad and Murtagh, Fionn
Year 2017
Volume 2(2)
Abstract Academic papers are growing at the rate of around 3% per year. Navigating this increasing information is challenging for a researcher seeking out high quality content. Our research explores relationships between traditional article level metrics, particularly citations, altmetrics and content quantities, to determine if relationships exist. Understanding these relationships may help to provide indicators to readers about article content prior to reading a paper and guide in paper selection. The research shows that there are positive strong relationships between citations and Mendeley readership counts but not between the citations and the Altmetric score or Twitter counts. This suggests that they are not related or other factors need to be taken into account when looking at altmetrics. We suggest that one of the factors that needs to be accounted for is popular subjects and further exploration is needed to understand how this influences altmetrics. The relationships between the quantities and article metrics are slight but more pronounced when we look at a subset of data with lower Altmetric scores and Twitter counts. There is a relationship between the number of references within an article and the way in which the citations are used within the article body. The articles studied are retrieved from PLoS (Public Library of Science) with the phrase text mining, and thus related content, in their subject or body.