COVID-19大流行早期推特用户的担忧——未来公共卫生传播的教训:一项基于推特的混合方法研究

IF 1 Q4 PRIMARY HEALTH CARE
Harshal B Sonekar, Kumaravel Ilangovan, Suganya Barani, Sendhilkumar Muthappan, Gowtham Sockalingam, Malathi Mathiyazhakan, Manickam Ponnaiah
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引用次数: 0

摘要

背景:在2019冠状病毒病期间,政府和公共卫生部门利用Twitter传播有关健康、意识和预防措施的信息。然而,在全球范围内,关于疫情演变阶段公众反应及其个人表现的信息资源有限。我们探讨了tweeple讨论的与COVID-19相关的话题。方法:我们使用Python 3.7中的Twitter应用程序编程接口(API)检索2019年12月25日至2020年3月26日期间包含“Corona”或“nCoV”或“Covid”或“SARS”或“病毒”关键字的英文推文,并带有预定义代码。使用关键字tweet的计数和比例以及关键字tweet的转发次数生成趋势图。我们对选出的1400条(每周四100条)推文进行了主题分析,并对主题进行了批判性评估。结果:我们发现推特用户在正式通知前一周就在讨论冠状病毒大流行。“冠状病毒”(60%)和“COVID”(26%)是最受欢迎的术语。我们构建了六个共同的主题,包括意识、情感、信仰、政治、经济和争议。早期推文的主要主题是新冠肺炎的经济影响和科学信息、污名和歧视、公众意识、个人反应、社会支持和阴谋论。结论:在2019冠状病毒病大流行的演变阶段,出现了快速的知识转移。Twitter作为一个充满活力的社交媒体,可以用于疾病暴发的早期识别,社区的感知和沟通,从而补充现有的疾病监测和管理系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Tweeples' concerns during the early phase of COVID-19 Pandemic - Lessons for the future public health communications: A Twitter-based mixed methods study.

Tweeples' concerns during the early phase of COVID-19 Pandemic - Lessons for the future public health communications: A Twitter-based mixed methods study.

Tweeples' concerns during the early phase of COVID-19 Pandemic - Lessons for the future public health communications: A Twitter-based mixed methods study.

Tweeples' concerns during the early phase of COVID-19 Pandemic - Lessons for the future public health communications: A Twitter-based mixed methods study.

Background: During COVID-19, the government and public health sectors used Twitter for disseminating information on health, awareness and preventing measures. However, resources on infodemics of the public responses and their personal expressions in the evolutionary stages of the pandemic at a global level is limited. We explored the topics discussed by the Tweeples related to COVID-19.

Methods: We retrieved English language tweets from 25 December 2019 to 26 March 2020 containing the keywords 'Corona' or 'nCoV' or 'Covid' or 'SARS' or 'virus' using the Twitter's application programme interface (API) in Python 3.7 with predefined codes. Trend graphs were generated using the counts and proportions of keyword tweets and the number of retweets of the keyword tweets. We performed thematic analysis with selected 1400 (100 from every Thursday) tweets for emerging topics and critically appraised the themes.

Results: We identified that Tweeples' were discussing the coronavirus pandemic a week before official notification. 'Corona' (60%) and 'COVID' (26%) were the most popular terms. We constructed six common themes including awareness, emotions, beliefs, politics, economy and controversies. Key topics of the tweets during the early stages were the economic impact and scientific information of COVID-19, stigma and discrimination, general awareness, personal reactions, social support and conspirational theories.

Conclusion: During the evolutionary phase of the COVID-19 pandemic, a rapid knowledge transition was observed. Twitter as a vibrant social media can be used for early identification of disease outbreak, perception and communication of the community, thus complementing the existing disease-surveillance and management systems.

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