Abstract

The use of social media assists in the distribution of information about COVID-19 to the general public and health professionals. Alternative-level metrics (Altmetrics) is an alternative method to traditional bibliometrics that assess the amount of sharing and spreading of a scientific article on social media platforms. Our objective was to characterize and compare traditional bibliometrics (citation-count) with newer metrics (Altmetric Attention Score) of the top 100 Altmetric scored COVID-19 articles. The 100 highest Altmetric Attention Score (AAS) articles were identified utilizing the Altmetric explorer in May 2020. AAS, journal name, and mentions from various social media databases (Twitter, Facebook, Wikipedia, Reddit, Mendeley, Dimension) of each article were collected. Citation-counts were collected from the Scopus database. The median AAS and citation-count were 4922.50 and 24.00, respectively. Of 100 articles, The New England Journal of Medicine published the most articles at 18% (18/100). Twitter was the most frequently used social media platform with 96.3% of the mentions (985,429/1,022,975). Positive correlations were seen between AAS and citation-count (r2=.0973; P=.002). Our research characterized the top 100 articles by AAS regarding COVID-19 in the Altmetric database. Altmetrics could complement with traditional citation-count when assessing the dissemination of an article regarding COVID-19. RR2-10.2196/21408.

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