Understanding reactions to swine flu, Ebola, and the Zika virus using Twitter data: an outlook for future infectious disease outbreaks

W. Ahmed, P. Bath
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Abstract

Infectious disease outbreaks are a serious public health threat which can disrupt world economies. This paper presents an in-depth qualitative analysis of n=15,415 tweets that relate to the peak of three major infectious diseases: the swine flu outbreak of 2009, the Ebola outbreak of 2014, and the Zika outbreak of 2016. Tweets were analysed using thematic analysis and a number of themes and sub-themes were identified. The results were brought together in an abstraction phase and the commonalities between the cases were studied. A notable similarity which emerged was the rate at which Twitter users expressed intense fear and panic akin to that of the phenomena of “moral panic” and the “outbreak narrative”. Our study also discusses the utility of using Twitter data for in-depth qualitative research as compared to traditional interview-methods. Our study is the largest in-depth analysis of tweets on infectious diseases and could inform public health strategies for future outbreaks such as the coronavirus outbreak.
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利用Twitter数据了解人们对猪流感、埃博拉和寨卡病毒的反应:对未来传染病爆发的展望
传染病爆发是一种严重的公共卫生威胁,可以扰乱世界经济。本文对2009年猪流感疫情、2014年埃博拉疫情和2016年寨卡疫情这三种主要传染病爆发高峰期的n= 15415条推文进行了深入的定性分析。使用主题分析对推文进行分析,并确定了一些主题和副主题。在抽象阶段将结果汇集在一起,并研究了案例之间的共性。一个值得注意的相似之处是,Twitter用户表达强烈恐惧和恐慌的频率与“道德恐慌”和“疫情叙事”现象类似。我们的研究还讨论了与传统的访谈方法相比,使用Twitter数据进行深入定性研究的效用。我们的研究是对传染病推文进行的最大规模的深入分析,可以为未来疫情(如冠状病毒爆发)的公共卫生战略提供信息。
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