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A rumor reversal model of online health information during the Covid-19 epidemic

The development of the Internet and social media has expanded the speed and scope of information dissemination, but not all widely disseminated information is true. Especially during the public health emergencies, the endogenous health information demand generated by the lack of scientific knowledge...

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Detalles Bibliográficos
Autores principales: Wang, Xiwei, Li, Yueqi, Li, Jiaxing, Liu, Yutong, Qiu, Chengcheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8441309/
https://www.ncbi.nlm.nih.gov/pubmed/34539040
http://dx.doi.org/10.1016/j.ipm.2021.102731
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author Wang, Xiwei
Li, Yueqi
Li, Jiaxing
Liu, Yutong
Qiu, Chengcheng
author_facet Wang, Xiwei
Li, Yueqi
Li, Jiaxing
Liu, Yutong
Qiu, Chengcheng
author_sort Wang, Xiwei
collection PubMed
description The development of the Internet and social media has expanded the speed and scope of information dissemination, but not all widely disseminated information is true. Especially during the public health emergencies, the endogenous health information demand generated by the lack of scientific knowledge of health information among online users stimulates the dissemination of health information by mass media while providing opportunities for rumor mongers to publish and spread online rumors. Invalid scientific knowledge and rumors will have a serious negative impact and disrupt social order during epidemic outbreaks such as COVID-19. Therefore, it is extremely important to construct an effective online rumor reversal model. The purpose of this study is to build an online rumor reversal model to control the spread of online rumors and reduce their negative impact. From the perspective of internal and external factors, based on the SIR model, this study constructed a G-SCNDR online rumor reversal model by adopting scientific knowledge level theory and an external online rumor control strategy. In this study, the G-SCNDR model is simulated, and a sensitivity analysis of the important parameters of the model is performed. The reversal efficiency of the G-SCNDR model can be improved by properly adopting the isolation-conversion strategy as the external control approach to online rumors with improving the popularization rate of the level of users' scientific knowledge and accelerating the transformation efficiency of official nodes. This study can help provide a better understanding of the process of online rumor spreading and reversing, as well as offering ceritain guidance and countermeasures for online rumor control during public health emergencies.
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spelling pubmed-84413092021-09-15 A rumor reversal model of online health information during the Covid-19 epidemic Wang, Xiwei Li, Yueqi Li, Jiaxing Liu, Yutong Qiu, Chengcheng Inf Process Manag Article The development of the Internet and social media has expanded the speed and scope of information dissemination, but not all widely disseminated information is true. Especially during the public health emergencies, the endogenous health information demand generated by the lack of scientific knowledge of health information among online users stimulates the dissemination of health information by mass media while providing opportunities for rumor mongers to publish and spread online rumors. Invalid scientific knowledge and rumors will have a serious negative impact and disrupt social order during epidemic outbreaks such as COVID-19. Therefore, it is extremely important to construct an effective online rumor reversal model. The purpose of this study is to build an online rumor reversal model to control the spread of online rumors and reduce their negative impact. From the perspective of internal and external factors, based on the SIR model, this study constructed a G-SCNDR online rumor reversal model by adopting scientific knowledge level theory and an external online rumor control strategy. In this study, the G-SCNDR model is simulated, and a sensitivity analysis of the important parameters of the model is performed. The reversal efficiency of the G-SCNDR model can be improved by properly adopting the isolation-conversion strategy as the external control approach to online rumors with improving the popularization rate of the level of users' scientific knowledge and accelerating the transformation efficiency of official nodes. This study can help provide a better understanding of the process of online rumor spreading and reversing, as well as offering ceritain guidance and countermeasures for online rumor control during public health emergencies. Elsevier Ltd. 2021-11 2021-08-24 /pmc/articles/PMC8441309/ /pubmed/34539040 http://dx.doi.org/10.1016/j.ipm.2021.102731 Text en © 2021 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
Wang, Xiwei
Li, Yueqi
Li, Jiaxing
Liu, Yutong
Qiu, Chengcheng
A rumor reversal model of online health information during the Covid-19 epidemic
title A rumor reversal model of online health information during the Covid-19 epidemic
title_full A rumor reversal model of online health information during the Covid-19 epidemic
title_fullStr A rumor reversal model of online health information during the Covid-19 epidemic
title_full_unstemmed A rumor reversal model of online health information during the Covid-19 epidemic
title_short A rumor reversal model of online health information during the Covid-19 epidemic
title_sort rumor reversal model of online health information during the covid-19 epidemic
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8441309/
https://www.ncbi.nlm.nih.gov/pubmed/34539040
http://dx.doi.org/10.1016/j.ipm.2021.102731
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