Document Type
Article
Version Deposited
Published Version
Publication Date
7-12-2023
Publication Title
JMIR Formative Research
DOI
10.2196/41388
Abstract
BACKGROUND: The use of social media assists in the distribution of information about COVID-19 to the general public and health professionals. Alternative-level metrics (i.e., Altmetrics) is an alternative method to traditional bibliometrics that assess the extent of dissemination of a scientific article on social media platforms.
OBJECTIVE: Our study objective was to characterize and compare traditional bibliometrics (citation count) with newer metrics (Altmetric Attention Score [AAS]) of the top 100 Altmetric-scored articles on COVID-19.
METHODS: The top 100 articles with the highest AAS were identified using the Altmetric explorer in May 2020. AAS, journal name, and mentions from various social media platforms (Twitter, Facebook, Wikipedia, Reddit, Mendeley, and Dimension) were collected for each article. Citation counts were collected from the Scopus database.
RESULTS: The median AAS and citation count were 4922.50 and 24.00, respectively. The New England Journal of Medicine published the most articles (18/100, 18%). Twitter was the most frequently used social media platform with 985,429 of 1,022,975 (96.3%) mentions. Positive correlations were observed between AAS and citation count (r2=0.0973; P=.002).
CONCLUSIONS: Our research characterized the top 100 COVID-19-related articles by AAS in the Altmetric database. Altmetrics could complement traditional citation count when assessing the dissemination of an article regarding COVID-19.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/21408.
Recommended Citation
Tornberg H, Moezinia C, Wei C, Bernstein SA, Wei C, Al-Beyati R, Quan T, Diemert DJ Assessment of the Dissemination of COVID-19–Related Articles Across Social Media: Altmetrics Study JMIR Form Res 2023;7:e41388
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Comments
©Haley Tornberg, Carine Moezinia, Chapman Wei, Simone A Bernstein, Chaplin Wei, Refka Al-Beyati, Theodore Quan, David J Diemert. Originally published in JMIR Formative Research (https://formative.jmir.org), 12.07.2023. This is an open-access article distributed under the terms of the Creative Commons Attribution License.