Sentiment Analysis of New Zealand Adults’ and Children’s Tweets Regarding the COVID-19 Vaccination Programme

dc.contributor.advisorMpofu, Charles
dc.contributor.authorAldahmash, Lamyaa
dc.date.accessioned2023-12-03T11:47:03Z
dc.date.available2023-12-03T11:47:03Z
dc.date.issued2023-12-02
dc.description.abstractThe SARS-CoV-2 virus, which caused the global COVID-19 pandemic, necessitated a significant worldwide response, with vaccination being a primary strategy. This dissertation explores the public sentiment towards New Zealand’s national vaccination campaign, through a machine learning analysis of large-scale text data gathered from the social media platform Twitter. Focusing on responses from both adults and children, this research aimed to assess the efficacy of health communication strategies and the wider acceptance of the vaccine within the community. The findings underscore a considerable disparity between policy decisions and public sentiment on Twitter, with a significant portion of the New Zealand population expressing negative views on vaccinations. Overall, this research reveals the need for enhanced public engagement, better communication, and more effective use of social media data by policymakers and healthcare professionals in order to address public concerns, mitigate fears, dispel misinformation, and ultimately increase vaccine uptake.
dc.format.extent67
dc.identifier.urihttps://hdl.handle.net/20.500.14154/70012
dc.language.isoen
dc.publisherSaudi Digital Library
dc.subjectCOVID-19 pandemic
dc.subjectvaccination
dc.subjectTwitter
dc.subjectNew Zealand’s national vaccination
dc.subjectMachine Learning Applications
dc.subjectSentiment Analysis
dc.subjectWorld Health Organization
dc.subjectPython
dc.titleSentiment Analysis of New Zealand Adults’ and Children’s Tweets Regarding the COVID-19 Vaccination Programme
dc.typeThesis
sdl.degree.departmentPublic Health
sdl.degree.disciplinePublic Health
sdl.degree.grantorAuckland University of Technology
sdl.degree.nameMaster's Degree

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