2019
DOI: 10.1111/hir.12247
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Novel insights into views towards H1N1 during the 2009 Pandemic: a thematic analysis of Twitter data

Abstract: Background Infectious disease outbreaks have the potential to cause a high number of fatalities and are a very serious public health risk. Objectives Our aim was to utilise an indepth method to study a period of time where the H1N1 Pandemic of 2009 was at its peak. Methods A data set of n = 214 784 tweets was retrieved and filtered, and the method of thematic analysis was used to analyse the data. Results Eight key themes emerged from the analysis of data: emotion and feeling, health related information, gener… Show more

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Cited by 91 publications
(97 citation statements)
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References 29 publications
(32 reference statements)
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“…Although no studies of Twitter during COVID-19 were revealed by our MEDLINE search, several previous studies have suggested a role for Twitter data during other public health outbreaks including Middle East respiratory syndrome, 23 SARS, 24 Ebola virus disease, 15 Zika virus, 25 H1N1 ('swine flu') 26 and H7N9 ('avian flu'). 27 Suggested roles for Twitter include infectious disease surveillance, predicting spread of disease, dissemination of public health information and assessing public views toward public health outbreaks.…”
Section: What Is Already Known On This Topicmentioning
confidence: 81%
See 1 more Smart Citation
“…Although no studies of Twitter during COVID-19 were revealed by our MEDLINE search, several previous studies have suggested a role for Twitter data during other public health outbreaks including Middle East respiratory syndrome, 23 SARS, 24 Ebola virus disease, 15 Zika virus, 25 H1N1 ('swine flu') 26 and H7N9 ('avian flu'). 27 Suggested roles for Twitter include infectious disease surveillance, predicting spread of disease, dissemination of public health information and assessing public views toward public health outbreaks.…”
Section: What Is Already Known On This Topicmentioning
confidence: 81%
“…27 Suggested roles for Twitter include infectious disease surveillance, predicting spread of disease, dissemination of public health information and assessing public views toward public health outbreaks. 15,[23][24][25][26][27]…”
Section: What Is Already Known On This Topicmentioning
confidence: 99%
“…Using thematic analysis with their data, Ahmed, Bath, Sbaffi and Demartini () present an examination of 214 784 tweets sent at the height of the H1N1 Pandemic. In addition to the eight themes which emerged from their thematic analysis, Ahmed et al.…”
Section: In This Issue…mentioning
confidence: 99%
“…In addition to the eight themes which emerged from their thematic analysis, Ahmed et al. 's () study presents an insight into the ways in which the public communicate on social media during disease outbreaks including misconceptions about disease hosts and transmission.…”
Section: In This Issue…mentioning
confidence: 99%
“…Non-protected tweets are publicly available and approximately 3% of tweets are voluntarily geotagged [5]. As Twitter has the advantage of real-time content availability, it has been harnessed during past infectious disease outbreaks to understand networks, gauge public knowledge, and forecast spread [6][7][8][9][10][11][12]. In recent studies, we have utilized Twitter to better understand critical social and behavioral outcomes such as suicide risk [13 14].…”
Section: Introductionmentioning
confidence: 99%
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