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Global misinformation spillovers in the online vaccination debate before and during COVID-19

Authors: Lenti, Jacopo;

Global misinformation spillovers in the online vaccination debate before and during COVID-19

Abstract

The dataset includes all the ids of the tweets analysed in the paper "Global misinformation spillovers in the online vaccination debate before and during COVID-19", divided by lang. They are all the tweets containing vaccines keywords in 18 different European languages, spanning the period October 2019 - March 2021 (excluded 2020 Jan - 2020 Jun). Note that a large fraction of the tweets can't be retrieved because of the suspension of the accounts and the removal of the posts by the users, so the study is only partially reproducible. The unzipped dataset has a dimension of 8,0G. The authors of the paper are: Lenti J, Mejova Y, Kalimeri K, Panisson A, Paolotti D, Tizzani M, Starnini M.

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selected citations
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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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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1
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