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Our data collection was driven by the goal of gathering a corpus of English-language tweets that would be informative of the online debate on COVID-19 vaccines worldwide. To that end, we used the Twitter API Search to collect tweets based on specific keywords related to COVID-19 vaccination. We built a list of such keywords that include terms related to both pro and anti-vaccine discourse as well as words related to the most well known COVID-19 vaccines available so far. Specifically, we consider the following list of keywords: vaccine, vaccination, anti-vaccination, antivax, anti-vaccine, anti-vax, anti-vaxxers, NoForcedVaccination, getvaccinated, pfizer, moderna, astrazeneca, covaxin, biontech, novavax, coronavac, sputnikv, bnt162b2. In total, we gathered over $12$ million tweets, covering 9 weeks, from December 1st, 2020 to January 31st, 2021. This is an important period that includes the launch of the first worldwide COVID-19 vaccination campaign (launched on December 8th in the United Kingdom), as well as several other important real-world events that influenced and dictated people's discussions. This dataset is aggregated by weeks and keywords. Only the tweets IDs are available following Twitter's Privacy Policy. Please cite as: MALAGOLI, L. G. ; STANCIOLI, J. ; VASCONCELOS, M. ; FERREIRA, C. H. ; SILVA, A. P. C. ; ALMEIDA, Jussara. A Look into COVID-19 Vaccination Debate on Twitter. In: 13th ACM Conference on Web Science, 2021.
Corona Virus, COVID-19, Vaccine, Twitter Dataset
Corona Virus, COVID-19, Vaccine, Twitter Dataset
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 17 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
| views | 13 | |
| downloads | 6 |

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