The relationship between citations, downloads and alternative metrics in rheumatology publications: a bibliometric study

Abstract

Objective: Scientific journals and authors are frequently judged on 'impact'. Commonly used traditional metrics are the Impact Factor and H-index. However, both take several years to formulate and have many limitations. Recently, Altmetric-a metric that measures impact in a non-traditional way-has gained popularity. This project aims to describe the relationships between subject matter, citations, downloads and Altmetric within rheumatology.

Methods: Data from publications in Rheumatology were used. Articles published from 2010 to 2015 were reviewed. Data were analysed using Stata 14.2 (StataCorp, College Station, TX, USA). Correlation between citations, downloads and Altmetric were quantified using linear regression, comparing across disease topics. Relationship between downloads and months since publications were described using negative binomial regression, clustering on individual articles.

Results: A total of 1460 Basic Science and Clinical Science articles were identified, with the number of citations, downloads and Altmetric scores. There were no correlations between disease topic and downloads (R2 = 0.016, P = 0.03), citations (R2 = 0.011, P = 0.29) or Altmetric (R2 = 0.025, P = 0.02). A statistically significant positive association was seen between the number of citations and downloads (R2 = 0.29, P < 0.001). No correlations were seen between Altmetric and downloads (R2 = 0.028, P < 0.001) or citations (R2 = 0.004, P = 0.445).

Conclusion: Disease area did not correlate with any of the metrics compared. Correlations were apparent with clear links between downloads and citations. Altmetric identified different articles as high impact compared with citation or download metrics. In conclusion: tweeting about your research does not appear to influence citations.

Keywords: altmetric; citations; download; research impact; twitter.