Health-Related Rumor Control through Social Collaboration Models: Lessons from Cases in China during the COVID-19 Pandemic

Widely spread health-related rumors may mislead the public, escalate social panic, compromise government credibility, and threaten public health. Social collaboration models that maximize the functions and advantages of various agents of socialization can be a promising way to control health-related...

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Main Authors: Feng Yang, Yunyue Ren, Shusheng Wang, Xiaoqian Zhang
Format: Article
Language:English
Published: MDPI AG 2022-08-01
Series:Healthcare
Subjects:
Online Access:https://www.mdpi.com/2227-9032/10/8/1475
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author Feng Yang
Yunyue Ren
Shusheng Wang
Xiaoqian Zhang
author_facet Feng Yang
Yunyue Ren
Shusheng Wang
Xiaoqian Zhang
author_sort Feng Yang
collection DOAJ
description Widely spread health-related rumors may mislead the public, escalate social panic, compromise government credibility, and threaten public health. Social collaboration models that maximize the functions and advantages of various agents of socialization can be a promising way to control health-related rumors. Existing research on health-related rumors, however, is limited in studying how various agents collaborate with each other to debunk rumors. This study utilizes content analysis to code the text data of health-related rumor cases in China during the COVID-19 pandemic. The study found that socialized rumor-debunking models could be divided into the following five categories: the government-led model, the media-led model, the scientific community-led model, the rumor-debunking platform-led model, and the multi-agent collaborative model. In addition, since rumors in public health crises often involve different objects, rumor refutation requires various information sources; therefore, different rumor-debunking models apply. This study verifies the value of socialized collaborative rumor debunking, advocates and encourages the participation of multiple agents of socialization and provides guidance for establishing a collaborative rumor-debunking model, thereby promoting efficient rumor-debunking methods and improving the healthcare of society.
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spelling doaj.art-a0cd1bfe2b834de9a0de6d812a370e1f2023-11-30T21:29:49ZengMDPI AGHealthcare2227-90322022-08-01108147510.3390/healthcare10081475Health-Related Rumor Control through Social Collaboration Models: Lessons from Cases in China during the COVID-19 PandemicFeng Yang0Yunyue Ren1Shusheng Wang2Xiaoqian Zhang3School of Public Administration, Sichuan University, Chengdu 610065, ChinaSchool of Public Administration, Sichuan University, Chengdu 610065, ChinaSchool of Public Administration, Sichuan University, Chengdu 610065, ChinaSchool of Information Studies, McGill University, Montreal, QC H3A 1X1, CanadaWidely spread health-related rumors may mislead the public, escalate social panic, compromise government credibility, and threaten public health. Social collaboration models that maximize the functions and advantages of various agents of socialization can be a promising way to control health-related rumors. Existing research on health-related rumors, however, is limited in studying how various agents collaborate with each other to debunk rumors. This study utilizes content analysis to code the text data of health-related rumor cases in China during the COVID-19 pandemic. The study found that socialized rumor-debunking models could be divided into the following five categories: the government-led model, the media-led model, the scientific community-led model, the rumor-debunking platform-led model, and the multi-agent collaborative model. In addition, since rumors in public health crises often involve different objects, rumor refutation requires various information sources; therefore, different rumor-debunking models apply. This study verifies the value of socialized collaborative rumor debunking, advocates and encourages the participation of multiple agents of socialization and provides guidance for establishing a collaborative rumor-debunking model, thereby promoting efficient rumor-debunking methods and improving the healthcare of society.https://www.mdpi.com/2227-9032/10/8/1475health rumorsrumor controlrumor-debunking modelcontent analysispandemicCOVID-19
spellingShingle Feng Yang
Yunyue Ren
Shusheng Wang
Xiaoqian Zhang
Health-Related Rumor Control through Social Collaboration Models: Lessons from Cases in China during the COVID-19 Pandemic
Healthcare
health rumors
rumor control
rumor-debunking model
content analysis
pandemic
COVID-19
title Health-Related Rumor Control through Social Collaboration Models: Lessons from Cases in China during the COVID-19 Pandemic
title_full Health-Related Rumor Control through Social Collaboration Models: Lessons from Cases in China during the COVID-19 Pandemic
title_fullStr Health-Related Rumor Control through Social Collaboration Models: Lessons from Cases in China during the COVID-19 Pandemic
title_full_unstemmed Health-Related Rumor Control through Social Collaboration Models: Lessons from Cases in China during the COVID-19 Pandemic
title_short Health-Related Rumor Control through Social Collaboration Models: Lessons from Cases in China during the COVID-19 Pandemic
title_sort health related rumor control through social collaboration models lessons from cases in china during the covid 19 pandemic
topic health rumors
rumor control
rumor-debunking model
content analysis
pandemic
COVID-19
url https://www.mdpi.com/2227-9032/10/8/1475
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