Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/33411
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dc.contributor.authorAhmed, Wasimen_UK
dc.contributor.authorBath, Peter Aen_UK
dc.contributor.authorSbaffi, Lauraen_UK
dc.contributor.authorDemartini, Gianlucaen_UK
dc.date.accessioned2021-10-12T07:09:10Z-
dc.date.available2021-10-12T07:09:10Z-
dc.date.issued2019-03en_UK
dc.identifier.urihttp://hdl.handle.net/1893/33411-
dc.description.abstractBackground: 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, general commentary and resources, media and health organisations, politics, country of origin, food, and humour and/or sarcasm. Discussion: 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. Conclusions: 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.en_UK
dc.language.isoenen_UK
dc.publisherWileyen_UK
dc.relationAhmed W, Bath PA, Sbaffi L & Demartini G (2019) Novel insights into views towards H1N1 during the 2009 Pandemic: a thematic analysis of Twitter data. Health Information and Libraries Journal, 36 (1), pp. 60-72. https://doi.org/10.1111/hir.12247en_UK
dc.rightsThis is the peer reviewed version of the following article: Ahmed, W., Bath, P.A., Sbaffi, L. and Demartini, G. (2019), Novel insights into views towards H1N1 during the 2009 Pandemic: a thematic analysis of Twitter data. Health Information and Libraries Journal, 36: 60-72., which has been published in final form at https://doi.org/10.1111/hir.12247. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for self-archiving.en_UK
dc.rights.urihttps://storre.stir.ac.uk/STORREEndUserLicence.pdfen_UK
dc.subjectpublic healthen_UK
dc.subjectqualitative researchen_UK
dc.subjectsocial mediaen_UK
dc.titleNovel insights into views towards H1N1 during the 2009 Pandemic: a thematic analysis of Twitter dataen_UK
dc.typeJournal Articleen_UK
dc.identifier.doi10.1111/hir.12247en_UK
dc.identifier.pmid30663232en_UK
dc.citation.jtitleHealth Information and Libraries Journalen_UK
dc.citation.issn1471-1842en_UK
dc.citation.issn1471-1834en_UK
dc.citation.volume36en_UK
dc.citation.issue1en_UK
dc.citation.spage60en_UK
dc.citation.epage72en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusAM - Accepted Manuscripten_UK
dc.contributor.funderUniversity of Sheffielden_UK
dc.author.emailwasim.ahmed@stir.ac.uken_UK
dc.citation.date20/01/2019en_UK
dc.contributor.affiliationNorthumbria Universityen_UK
dc.contributor.affiliationUniversity of Sheffielden_UK
dc.contributor.affiliationUniversity of Sheffielden_UK
dc.contributor.affiliationUniversity of Queenslanden_UK
dc.identifier.isiWOS:000459807700004en_UK
dc.identifier.scopusid2-s2.0-85060343813en_UK
dc.identifier.wtid1760279en_UK
dc.contributor.orcid0000-0001-8923-1865en_UK
dc.date.accepted2018-12-05en_UK
dcterms.dateAccepted2018-12-05en_UK
dc.date.filedepositdate2021-10-11en_UK
rioxxterms.apcnot requireden_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionAMen_UK
local.rioxx.authorAhmed, Wasim|0000-0001-8923-1865en_UK
local.rioxx.authorBath, Peter A|en_UK
local.rioxx.authorSbaffi, Laura|en_UK
local.rioxx.authorDemartini, Gianluca|en_UK
local.rioxx.projectProject ID unknown|University of Sheffield|http://dx.doi.org/10.13039/501100000858en_UK
local.rioxx.freetoreaddate2021-10-11en_UK
local.rioxx.licencehttps://storre.stir.ac.uk/STORREEndUserLicence.pdf|2021-10-11|en_UK
local.rioxx.filenameAhmed-etal-HILJ-2019.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source1471-1842en_UK
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