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Sharing of retracted COVID-19 articles: an altmetric study.
Shamsi, Amrollah; Lund, Brady Daniel; SeyyedHosseini, Shohreh.
  • Shamsi A; shamsiamrollah@gmail.com, Independent Research, Bushehr, Iran.
  • Lund BD; blund2@g.emporia.edu, School of Library and Information Management, Emporia State University, Emporia, KS.
  • SeyyedHosseini S; tanin64@gmail.com, Knowledge and Information Science, Bushehr University of Medical Sciences, Bushehr, Iran.
J Med Libr Assoc ; 110(1): 97-102, 2022 Jan 01.
Article in English | MEDLINE | ID: covidwho-1835456
ABSTRACT

OBJECTIVE:

This study examines the extent to which retracted articles pertaining to COVID-19 have been shared via social and mass media based on altmetric scores.

METHODS:

Seventy-one retracted articles related to COVID-19 were identified from relevant databases, of which thirty-nine had an Altmetric Attention Score obtained using the Altmetrics Bookmarklet. Data extracted from the articles include overall attention score and demographics of sharers (e.g., geographic location, professional affiliation).

RESULTS:

Retracted articles related to COVID-19 were shared tens of thousands of times to an audience of potentially hundreds of millions of readers and followers. Twitter was the largest medium for sharing these articles, and the United States was the country with the most sharers. While general members of the public were the largest proportion of sharers, researchers and professionals were not immune to sharing these articles on social media and on websites, blogs, or news media.

CONCLUSIONS:

These findings have potential implications for better understanding the spread of misleading or false information perpetuated in retracted scholarly publications. They emphasize the importance of quality peer review and research ethics among journals and responsibility among individuals who wish to share research findings.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Media / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: J Med Libr Assoc Journal subject: Library Science Year: 2022 Document Type: Article Affiliation country: Jmla.2022.1269

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Media / COVID-19 Type of study: Prognostic study Limits: Humans Language: English Journal: J Med Libr Assoc Journal subject: Library Science Year: 2022 Document Type: Article Affiliation country: Jmla.2022.1269