{"title":"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","authors":"W. Ahmed, P. Bath","doi":"10.15626/ishimr.2020.04","DOIUrl":null,"url":null,"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.","PeriodicalId":404498,"journal":{"name":"Proceedings of the 18th international symposium on health information management research","volume":"84 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Understanding reactions to swine flu, Ebola, and the Zika virus using Twitter data: an outlook for future infectious disease outbreaks\",\"authors\":\"W. Ahmed, P. Bath\",\"doi\":\"10.15626/ishimr.2020.04\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":404498,\"journal\":{\"name\":\"Proceedings of the 18th international symposium on health information management research\",\"volume\":\"84 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 18th international symposium on health information management research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15626/ishimr.2020.04\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 18th international symposium on health information management research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15626/ishimr.2020.04","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Understanding reactions to swine flu, Ebola, and the Zika virus using Twitter data: an outlook for future infectious disease outbreaks
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.