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Does the COVID-19 Vaccine Still Work That "Most of the Confirmed Cases Had Been Vaccinated"? A Content Analysis of Vaccine Effectiveness Discussion on Sina Weibo during the Outbreak of COVID-19 in Nanjing.“大多数确诊病例都已接种疫苗”,那么新冠疫苗还有效吗?对南京疫情期间新浪微博中疫苗有效性讨论的内容分析。
Int J Environ Res Public Health. 2021 Dec 26;19(1):241. doi: 10.3390/ijerph19010241.
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Social media and attitudes towards a COVID-19 vaccination: A systematic review of the literature.社交媒体与对新冠疫苗接种的态度:文献系统综述
EClinicalMedicine. 2022 Jun;48:101454. doi: 10.1016/j.eclinm.2022.101454. Epub 2022 May 20.
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本文引用的文献

1
Characterizing Discourse about COVID-19 Vaccines: A Reddit Version of the Pandemic Story.新冠疫苗相关话语的特征分析:Reddit 版的大流行故事
Health Data Sci. 2021 Aug 27;2021:9837856. doi: 10.34133/2021/9837856. eCollection 2021.
2
COVID-19 Vaccine and Social Media in the U.S.: Exploring Emotions and Discussions on Twitter.美国的新冠疫苗与社交媒体:探索推特上的情绪与讨论
Vaccines (Basel). 2021 Sep 23;9(10):1059. doi: 10.3390/vaccines9101059.
3
Attitudes, acceptance and hesitancy among the general population worldwide to receive the COVID-19 vaccines and their contributing factors: A systematic review.全球普通人群对接种新冠疫苗的态度、接受程度和犹豫情况及其影响因素:一项系统综述
EClinicalMedicine. 2021 Oct;40:101113. doi: 10.1016/j.eclinm.2021.101113. Epub 2021 Sep 2.
4
Analyzing Social Media to Explore the Attitudes and Behaviors Following the Announcement of Successful COVID-19 Vaccine Trials: Infodemiology Study.分析社交媒体以探究新冠病毒疫苗试验成功宣布后的态度和行为:信息流行病学研究
JMIR Infodemiology. 2021 Aug 12;1(1):e28800. doi: 10.2196/28800. eCollection 2021 Jan-Dec.
5
Cross-Platform Comparative Study of Public Concern on Social Media during the COVID-19 Pandemic: An Empirical Study Based on Twitter and Weibo.社交媒体平台在新冠疫情期间公众关注度的跨平台比较研究:基于 Twitter 和微博的实证研究
Int J Environ Res Public Health. 2021 Jun 16;18(12):6487. doi: 10.3390/ijerph18126487.
6
COVID-19 Vaccine-Related Discussion on Twitter: Topic Modeling and Sentiment Analysis.新冠疫苗相关推文的讨论:主题建模和情感分析。
J Med Internet Res. 2021 Jun 29;23(6):e24435. doi: 10.2196/24435.
7
Tweet Topics and Sentiments Relating to COVID-19 Vaccination Among Australian Twitter Users: Machine Learning Analysis.澳大利亚推特用户与 COVID-19 疫苗接种相关的推文主题和情绪:机器学习分析。
J Med Internet Res. 2021 May 19;23(5):e26953. doi: 10.2196/26953.
8
People's Willingness to Vaccinate Against COVID-19 Despite Their Safety Concerns: Twitter Poll Analysis.尽管存在安全顾虑,但人们对接种 COVID-19 疫苗的意愿:Twitter 民意调查分析。
J Med Internet Res. 2021 Apr 29;23(4):e28973. doi: 10.2196/28973.
9
Measuring the impact of COVID-19 vaccine misinformation on vaccination intent in the UK and USA.测量 COVID-19 疫苗错误信息对英国和美国疫苗接种意愿的影响。
Nat Hum Behav. 2021 Mar;5(3):337-348. doi: 10.1038/s41562-021-01056-1. Epub 2021 Feb 5.
10
A Novel Machine Learning Framework for Comparison of Viral COVID-19-Related Sina Weibo and Twitter Posts: Workflow Development and Content Analysis.一种用于比较病毒性 COVID-19 相关微博和推特帖子的新型机器学习框架:工作流程开发和内容分析。
J Med Internet Res. 2021 Jan 6;23(1):e24889. doi: 10.2196/24889.

“大多数确诊病例都已接种疫苗”,那么新冠疫苗还有效吗?对南京疫情期间新浪微博中疫苗有效性讨论的内容分析。

Does the COVID-19 Vaccine Still Work That "Most of the Confirmed Cases Had Been Vaccinated"? A Content Analysis of Vaccine Effectiveness Discussion on Sina Weibo during the Outbreak of COVID-19 in Nanjing.

机构信息

School of Journalism and Communication, Nanjing Normal University, Nanjing 210097, China.

School of Media and Communication, Shanghai Jiao Tong University, Shanghai 200240, China.

出版信息

Int J Environ Res Public Health. 2021 Dec 26;19(1):241. doi: 10.3390/ijerph19010241.

DOI:10.3390/ijerph19010241
PMID:35010501
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8750531/
Abstract

In July 2021, breakthrough cases were reported in the outbreak of COVID-19 in Nanjing, sparking concern and discussion about the vaccine's effectiveness and becoming a trending topic on Sina Weibo. In order to explore public attitudes towards the COVID-19 vaccine and their emotional orientations, we collected 1542 posts under the trending topic through data mining. We set up four categories of attitudes towards COVID-19 vaccines, and used a big data analysis tool to code and manually checked the coding results to complete the content analysis. The results showed that 45.14% of the Weibo posts ( = 1542) supported the COVID-19 vaccine, 12.97% were neutral, and 7.26% were doubtful, which indicated that the public did not question the vaccine's effectiveness due to the breakthrough cases in Nanjing. There were 66.47% posts that reflected significant negative emotions. Among these, 50.44% of posts with negative emotions were directed towards the media, 25.07% towards the posting users, and 11.51% towards the public, which indicated that the negative emotions were not directed towards the COVID-19 vaccine. External sources outside the vaccine might cause vaccine hesitancy. Public opinions expressed in online media reflect the public's cognition and attitude towards vaccines and their core needs in terms of information. Therefore, online public opinion monitoring could be an essential way to understand the opinions and attitudes towards public health issues.

摘要

2021 年 7 月,南京出现新冠肺炎疫情突破病例,引发了公众对疫苗有效性的关注和讨论,成为微博热搜话题。为了探讨公众对新冠疫苗的态度及其情绪取向,我们通过数据挖掘收集了该话题下的 1542 条微博。我们设立了对新冠疫苗的四种态度类别,利用大数据分析工具进行编码,并对编码结果进行人工检查,完成内容分析。结果显示,在 1542 条微博中,45.14%(=1542)的帖子支持新冠疫苗,12.97%的帖子持中立态度,7.26%的帖子对疫苗持怀疑态度,这表明公众并没有因为南京的突破病例而对疫苗的有效性产生质疑。有 66.47%的帖子反映出明显的负面情绪。其中,50.44%的负面情绪帖子针对媒体,25.07%的帖子针对发帖用户,11.51%的帖子针对公众,这表明负面情绪并不是针对新冠疫苗的。疫苗之外的外部因素可能会导致疫苗犹豫。网络媒体上表达的公众意见反映了公众对疫苗的认知和态度,以及他们在信息方面的核心需求。因此,在线舆情监测可能是了解公众对公共卫生问题的意见和态度的重要途径。