Newcastle Business School, Northumbria University, Newcastle upon Tyne, UK.
Information School, University of Sheffield, Sheffield, UK.
Health Info Libr J. 2019 Mar;36(1):60-72. doi: 10.1111/hir.12247. Epub 2019 Jan 20.
Infectious disease outbreaks have the potential to cause a high number of fatalities and are a very serious public health risk.
Our aim was to utilise an indepth method to study a period of time where the H1N1 Pandemic of 2009 was at its peak.
A data set of n = 214 784 tweets was retrieved and filtered, and the method of thematic analysis was used to analyse the data.
Eight key themes emerged from the analysis of data: emotion and feeling, health related information, general commentary and resources, media and health organisations, politics, country of origin, food, and humour and/or sarcasm.
A major novel finding was that due to the name 'swine flu', Twitter users had the belief that pigs and pork could host and/or transmit the virus. Our paper also considered the methodological implications for the wider field of library and information science as well as specific implications for health information and library workers.
Novel insights were derived on how users communicate about disease outbreaks on social media platforms. Our study also provides an innovative methodological contribution because it was found that by utilising an indepth method it was possible to extract greater insight into user communication.
传染病疫情有可能导致大量死亡，是非常严重的公共卫生风险。
我们旨在利用深入的方法研究 2009 年 H1N1 大流行的高峰期。
检索并过滤了 n=214784 条推文的数据集，并使用主题分析方法对数据进行分析。
从数据分析中出现了八个关键主题：情感和感觉、与健康相关的信息、一般评论和资源、媒体和卫生组织、政治、原籍国、食品以及幽默和/或讽刺。
一个主要的新发现是，由于“猪流感”这个名称，Twitter 用户认为猪和猪肉可以携带和/或传播病毒。我们的论文还考虑了图书馆和信息科学领域更广泛的方法学意义，以及对健康信息和图书馆工作人员的具体意义。
从社交媒体平台上用户如何交流疾病爆发方面得出了新颖的见解。我们的研究还提供了一种创新的方法学贡献，因为发现通过利用深入的方法，可以更深入地了解用户的交流。
