EconPapers    
Economics at your fingertips  
 

The variant of efforts avoiding strain: successful correction of a scientific discourse related to COVID-19

Dongwoo Lim (), Fujio Toriumi, Mitsuo Yoshida, Mikihito Tanaka and Kunhao Yang
Additional contact information
Dongwoo Lim: Tsuda University
Fujio Toriumi: The University of Tokyo
Mitsuo Yoshida: University of Tsukuba
Mikihito Tanaka: Waseda University
Kunhao Yang: Yamaguchi University

Journal of Computational Social Science, 2024, vol. 7, issue 1, No 1, 21 pages

Abstract: Abstract This study focuses on how scientifically accurate information is disseminated through social media, and how misinformation can be corrected. We have identified examples on Twitter where scientific terms that have been widely misused have been rectified and replaced by scientifically accurate terms through the interaction of users. The results show that the percentage of accurate terms (“variant” or “COVID-19 variant”) being used instead of the inaccurate terms (“strain”) on Twitter has already increased since the end of December 2020. This was about a month before the release of an official statement by the Japanese Association for Infectious Diseases regarding the accurate terminology, and the use of terms on social media was faster than it was in television. Some Twitter users who quickly started using the accurate term were more likely to retweet messages sent by leading influencers on Twitter, rather than messages sent by traditional media or portal sites. However, a few Twitter users continued to use wrong terms even after March 2021, even though the use of the accurate terms was widespread. This study empirically verified that self-correction occurs even on Twitter, and also suggested that influencers with expertise can influence the direction of public opinion on social media.

Keywords: Dissemination of expertise; Correction of misinformation; COVID-19 variant; Self-correction; Social media influencers (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s42001-023-00223-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jcsosc:v:7:y:2024:i:1:d:10.1007_s42001-023-00223-w

Ordering information: This journal article can be ordered from
http://www.springer. ... iences/journal/42001

DOI: 10.1007/s42001-023-00223-w

Access Statistics for this article

Journal of Computational Social Science is currently edited by Takashi Kamihigashi

More articles in Journal of Computational Social Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-20
Handle: RePEc:spr:jcsosc:v:7:y:2024:i:1:d:10.1007_s42001-023-00223-w