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Investigation of the determinants for misinformation correction effectiveness on social media during COVID-19 pandemic
The rapid dissemination of misinformation in social media during the COVID-19 pandemic triggers panic and threatens the pandemic preparedness and control. Correction is a crucial countermeasure to debunk misperceptions. However, the effective mechanism of correction on social media is not fully veri...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8979789/ https://www.ncbi.nlm.nih.gov/pubmed/35400028 http://dx.doi.org/10.1016/j.ipm.2022.102935 |
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author | Zhang, Yuqi Guo, Bin Ding, Yasan Liu, Jiaqi Qiu, Chen Liu, Sicong Yu, Zhiwen |
author_facet | Zhang, Yuqi Guo, Bin Ding, Yasan Liu, Jiaqi Qiu, Chen Liu, Sicong Yu, Zhiwen |
author_sort | Zhang, Yuqi |
collection | PubMed |
description | The rapid dissemination of misinformation in social media during the COVID-19 pandemic triggers panic and threatens the pandemic preparedness and control. Correction is a crucial countermeasure to debunk misperceptions. However, the effective mechanism of correction on social media is not fully verified. Previous works focus on psychological theories and experimental studies, while the applicability of conclusions to the actual social media is unclear. This study explores determinants governing the effectiveness of misinformation corrections on social media with a combination of a data-driven approach and related theories on psychology and communication. Specifically, referring to the Backfire Effect, Source Credibility, and Audience’s role in dissemination theories, we propose five hypotheses containing seven potential factors (regarding correction content and publishers’ influence), e.g., the proportion of original misinformation and warnings of misinformation. Then, we obtain 1487 significant COVID-19 related corrections on Microblog between January 1st, 2020 and April 30th, 2020, and conduct annotations, which characterize each piece of correction based on the aforementioned factors. We demonstrate several promising conclusions through a comprehensive analysis of the dataset. For example, mentioning excessive original misinformation in corrections would not undermine people’s believability within a short period after reading; warnings of misinformation in a demanding tone make correction worse; determinants of correction effectiveness vary among different topics of misinformation. Finally, we build a regression model to predict correction effectiveness. These results provide practical suggestions on misinformation correction on social media, and a tool to guide practitioners to revise corrections before publishing, leading to ideal efficacies. |
format | Online Article Text |
id | pubmed-8979789 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89797892022-04-05 Investigation of the determinants for misinformation correction effectiveness on social media during COVID-19 pandemic Zhang, Yuqi Guo, Bin Ding, Yasan Liu, Jiaqi Qiu, Chen Liu, Sicong Yu, Zhiwen Inf Process Manag Article The rapid dissemination of misinformation in social media during the COVID-19 pandemic triggers panic and threatens the pandemic preparedness and control. Correction is a crucial countermeasure to debunk misperceptions. However, the effective mechanism of correction on social media is not fully verified. Previous works focus on psychological theories and experimental studies, while the applicability of conclusions to the actual social media is unclear. This study explores determinants governing the effectiveness of misinformation corrections on social media with a combination of a data-driven approach and related theories on psychology and communication. Specifically, referring to the Backfire Effect, Source Credibility, and Audience’s role in dissemination theories, we propose five hypotheses containing seven potential factors (regarding correction content and publishers’ influence), e.g., the proportion of original misinformation and warnings of misinformation. Then, we obtain 1487 significant COVID-19 related corrections on Microblog between January 1st, 2020 and April 30th, 2020, and conduct annotations, which characterize each piece of correction based on the aforementioned factors. We demonstrate several promising conclusions through a comprehensive analysis of the dataset. For example, mentioning excessive original misinformation in corrections would not undermine people’s believability within a short period after reading; warnings of misinformation in a demanding tone make correction worse; determinants of correction effectiveness vary among different topics of misinformation. Finally, we build a regression model to predict correction effectiveness. These results provide practical suggestions on misinformation correction on social media, and a tool to guide practitioners to revise corrections before publishing, leading to ideal efficacies. Elsevier Ltd. 2022-05 2022-04-05 /pmc/articles/PMC8979789/ /pubmed/35400028 http://dx.doi.org/10.1016/j.ipm.2022.102935 Text en © 2022 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Zhang, Yuqi Guo, Bin Ding, Yasan Liu, Jiaqi Qiu, Chen Liu, Sicong Yu, Zhiwen Investigation of the determinants for misinformation correction effectiveness on social media during COVID-19 pandemic |
title | Investigation of the determinants for misinformation correction effectiveness on social media during COVID-19 pandemic |
title_full | Investigation of the determinants for misinformation correction effectiveness on social media during COVID-19 pandemic |
title_fullStr | Investigation of the determinants for misinformation correction effectiveness on social media during COVID-19 pandemic |
title_full_unstemmed | Investigation of the determinants for misinformation correction effectiveness on social media during COVID-19 pandemic |
title_short | Investigation of the determinants for misinformation correction effectiveness on social media during COVID-19 pandemic |
title_sort | investigation of the determinants for misinformation correction effectiveness on social media during covid-19 pandemic |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8979789/ https://www.ncbi.nlm.nih.gov/pubmed/35400028 http://dx.doi.org/10.1016/j.ipm.2022.102935 |
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