Assessment of the Dissemination of COVID-19-Related Articles Across Social Media: Altmetrics Study.

作者信息

Tornberg Haley, Moezinia Carine, Wei Chapman, Bernstein Simone A, Wei Chaplin, Al-Beyati Refka, Quan Theodore, Diemert David J

机构信息

Cooper Medical School of Rowan University, Camden, NJ, United States.

Department of Medicine, Hospital for Special Surgery, New York, NY, United States.

出版信息

JMIR Form Res. 2023 Jul 12;7:e41388. 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 (ie, 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. TheNew 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 (r=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.

摘要

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