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dc.contributor.advisorRypdal, Martin
dc.contributor.authorHolmstrand, Inga Setså
dc.date.accessioned2018-08-22T08:52:27Z
dc.date.available2018-08-22T08:52:27Z
dc.date.issued2018-06-01
dc.description.abstractHaving the flu is something that everyone is familiar with, and the influenza season hits every year. The intensity and timing vary from year to year driven by climatic conditions and antigenic evolution, through mechanisms that are only partially understood. Most research agree that the virus originates in East and South-East (E-SE) Asia and spread throughout the world through human movement. In this thesis we explore the possibility of modelling this circulation pattern using a simple semi-stochastic mathematical model. Interestingly, this model exhibits chaotic behavior and is unable to confirm the above mentioned hypothesis. A separate approach is to analyze influenza incidence data. However, these data are subject to substantial underreporting (or complete lack of reporting) during the low-seasons. Some recent works have suggested using social media data to obtain proxies of influenza-like illness (ILI) data. In this thesis we discuss if it is possible to discern pattern or tendencies using data from Twitter. As the data used is collected only during a short time window, we can only say something about the feasibility of using this approach to analyze the global circulation of influenza viruses.en_US
dc.identifier.urihttps://hdl.handle.net/10037/13529
dc.language.isoengen_US
dc.publisherUiT The Arctic University of Norwayen_US
dc.publisherUiT Norges arktiske universiteten_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2018 The Author(s)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/3.0en_US
dc.rightsAttribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)en_US
dc.subject.courseIDEOM-3901
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Matematikk: 410::Anvendt matematikk: 413en_US
dc.subjectVDP::Mathematics and natural science: 400::Mathematics: 410::Applied mathematics: 413en_US
dc.subjectTwitteren_US
dc.subjectCirculation patternen_US
dc.subjectILIen_US
dc.subjectInfluenzaen_US
dc.titleOn the Feasibility of Using Twitter Data to Assess the Global Circulation Patterns of Influenza Virusesen_US
dc.typeMaster thesisen_US
dc.typeMastergradsoppgaveen_US


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Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)