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• W4386325810 abstract "Abstract More than six and half million people have died as a result of the COVID-19 pandemic till Dec 2022. Vaccination is the most effective means to prevent mortality and infection attributed to COVID-19. Identifying public attitudes and perceptions on COVID-19 vaccination is essential to strengthening the vaccination programmes. This study aims to identify attitudes and perceptions of twitter users towards COVID-19 vaccinations in four different countries. A sentiment analysis of 663,377 tweets from October 2020 to September 2022 from four different countries (i.e., India, South Africa, UK, and Australia) was conducted. Text mining using roBERTA (Robustly Optimized Bert Pretraining approach) python library was used to identify the polarity of people’s attitude as negative, positive or neutral based on tweets. A sample of 2000 tweets (500 from each country) were thematically analysed to explore the people’s perception concerning COVID-19 vaccines across the countries. The attitudes towards COVID-19 vaccines varied by countries. Negative attitudes were observed to be highest in India (58.48%), followed by United Kingdom (33.22%), Australia (31.42%) and South Africa (28.88%). Positive attitudes towards vaccines were highest in the United Kingdom (21.09%). The qualitative analysis yielded eight themes namely (i) vaccine shortages, (ii) vaccine side-effects, (iii) distrust on COVID-19 vaccines, (iv) voices for vaccine equity, (v) awareness about vaccines, (vi) myth busters, (vii) vaccines work and (viii) vaccines are safe. The twitter discourse reflected the evolving situation of COVID-19 pandemic and vaccination strategies, lacunae and positives in the respective countries studied." @default.
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• W4386325810 date "2023-08-31" @default.
• W4386325810 modified "2023-09-30" @default.
• W4386325810 title "People’s perceptions on COVID-19 vaccination: an analysis of twitter discourse from four countries" @default.
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• W4386325810 doi "https://doi.org/10.1038/s41598-023-41478-7" @default.
• W4386325810 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37653001" @default.
• W4386325810 hasPublicationYear "2023" @default.
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