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Identifying features of source and message that influence the retweeting of health information on social media during the COVID-19 pandemic

BACKGROUND: Social media has become an essential tool to implement risk communication, giving health information could gain more exposure by retweeting during the COVID-19 pandemic. METHODS: Content analysis was conducted to scrutinize the official (national and provincial) public health agencies’ W...

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Autores principales: Xie, Jingzhong, Liu, Liqun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9026044/
https://www.ncbi.nlm.nih.gov/pubmed/35459154
http://dx.doi.org/10.1186/s12889-022-13213-w
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author Xie, Jingzhong
Liu, Liqun
author_facet Xie, Jingzhong
Liu, Liqun
author_sort Xie, Jingzhong
collection PubMed
description BACKGROUND: Social media has become an essential tool to implement risk communication, giving health information could gain more exposure by retweeting during the COVID-19 pandemic. METHODS: Content analysis was conducted to scrutinize the official (national and provincial) public health agencies’ Weibo posts (n = 4396) to identify features of information sources and message features (structure, style content). The Zero-Inflated Negative Binomial (ZINB) model was adopted to analyze the association between these features and the frequency of the retweeted messages. RESULTS: Results indicated that features of source and health information, such as structure, style, and content, were correlated to retweeting. The results of IRR further suggested that compared to provincial accounts, messages from national health authorities’ accounts gained more retweeting. Regarding the information features, messages with hashtags#, picture, video have been retweeted more often than messages without any of these features respectively, while messages with hyperlinks received fewer retweets than messages without hyperlinks. In terms of the information structure, messages with the sentiment (!) have been retweeted more frequently than messages without sentiment. Concerning content, messages containing severity, reassurance, efficacy, and action frame have been retweeted with higher frequency, while messages with uncertainty frames have been retweeted less often. CONCLUSIONS: Health organizations and medical professionals should pay close attention to the features of health information sources, structures, style, and content to satisfy the public’s information needs and preferences to promote the public's health engagement. Designing suitable information systems and promoting health communication strategies during different pandemic stages may improve public awareness of the COVID-19, alleviate negative emotions, and promote preventive measures to curb the spread of the virus.
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spelling pubmed-90260442022-04-22 Identifying features of source and message that influence the retweeting of health information on social media during the COVID-19 pandemic Xie, Jingzhong Liu, Liqun BMC Public Health Research BACKGROUND: Social media has become an essential tool to implement risk communication, giving health information could gain more exposure by retweeting during the COVID-19 pandemic. METHODS: Content analysis was conducted to scrutinize the official (national and provincial) public health agencies’ Weibo posts (n = 4396) to identify features of information sources and message features (structure, style content). The Zero-Inflated Negative Binomial (ZINB) model was adopted to analyze the association between these features and the frequency of the retweeted messages. RESULTS: Results indicated that features of source and health information, such as structure, style, and content, were correlated to retweeting. The results of IRR further suggested that compared to provincial accounts, messages from national health authorities’ accounts gained more retweeting. Regarding the information features, messages with hashtags#, picture, video have been retweeted more often than messages without any of these features respectively, while messages with hyperlinks received fewer retweets than messages without hyperlinks. In terms of the information structure, messages with the sentiment (!) have been retweeted more frequently than messages without sentiment. Concerning content, messages containing severity, reassurance, efficacy, and action frame have been retweeted with higher frequency, while messages with uncertainty frames have been retweeted less often. CONCLUSIONS: Health organizations and medical professionals should pay close attention to the features of health information sources, structures, style, and content to satisfy the public’s information needs and preferences to promote the public's health engagement. Designing suitable information systems and promoting health communication strategies during different pandemic stages may improve public awareness of the COVID-19, alleviate negative emotions, and promote preventive measures to curb the spread of the virus. BioMed Central 2022-04-22 /pmc/articles/PMC9026044/ /pubmed/35459154 http://dx.doi.org/10.1186/s12889-022-13213-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Xie, Jingzhong
Liu, Liqun
Identifying features of source and message that influence the retweeting of health information on social media during the COVID-19 pandemic
title Identifying features of source and message that influence the retweeting of health information on social media during the COVID-19 pandemic
title_full Identifying features of source and message that influence the retweeting of health information on social media during the COVID-19 pandemic
title_fullStr Identifying features of source and message that influence the retweeting of health information on social media during the COVID-19 pandemic
title_full_unstemmed Identifying features of source and message that influence the retweeting of health information on social media during the COVID-19 pandemic
title_short Identifying features of source and message that influence the retweeting of health information on social media during the COVID-19 pandemic
title_sort identifying features of source and message that influence the retweeting of health information on social media during the covid-19 pandemic
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9026044/
https://www.ncbi.nlm.nih.gov/pubmed/35459154
http://dx.doi.org/10.1186/s12889-022-13213-w
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