Wash your hands: CDC, WHO, and NHS tweets in the #COVID19 pandemic

Katherine A Ireland
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引用次数: 0

Abstract

This work tracks public health messaging and evidence of stability and change in corpora of the Centers for Disease Control and Prevention (CDC), World Health Organization (WHO), and National Health Service (NHS) official account tweets throughout 2020. Using corpus-based methods, including keyword analysis, major similarities and differences are identified across tweets by each organization over time. Larger macro-level and micro-level discourses and linguistic patterns are revealed, with specific applications relevant to public health and governmental messaging, especially regarding risk and health communication. Findings include the NHS providing the most comprehensive and varied messaging out of each organization, including references to recommended actions, communities and individuals, and information. The WHO focuses predominantly on cases and region-specific information, while the CDC includes a variety of information, with a US-internal focus. Applications include further recommendations for public health communication, including the necessity of diverse linguistic patterns and interactive messaging tactics for governmental organizations.

洗手:疾病预防控制中心、世卫组织和国家医疗服务体系在 #COVID19 大流行中的推文
这项研究追踪了 2020 年间疾病控制和预防中心(CDC)、世界卫生组织(WHO)和国家卫生服务系统(NHS)官方账户推文语料库中的公共卫生信息以及稳定和变化的证据。通过使用基于语料库的方法(包括关键词分析),确定了各组织在不同时期推文中的主要相似点和不同点。研究揭示了更大的宏观和微观层面的话语和语言模式,并将其具体应用于公共卫生和政府信息传播,尤其是风险和健康传播方面。研究结果表明,在每个组织中,英国国家医疗服务系统(NHS)提供的信息最全面、最多样,包括对建议行动、社区和个人以及信息的提及。世卫组织主要侧重于病例和特定地区的信息,而疾病预防控制中心则包括各种信息,以美国国内信息为主。这些应用包括对公共卫生传播的进一步建议,包括政府组织采用多样化语言模式和互动信息传递策略的必要性。
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来源期刊
Applied Corpus Linguistics
Applied Corpus Linguistics Linguistics and Language
CiteScore
1.30
自引率
0.00%
发文量
0
审稿时长
70 days
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