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dc.creatorMutlu, Ece C.
dc.creatorOghaz, Toktam
dc.creatorJasser, Jasser
dc.creatorTutunculer, Ege
dc.creatorRajabi, Amirarsalan
dc.creatorTayebi, Aida
dc.creatorOzmen, Ozlem
dc.creatorGaribay, Ivan
dc.date.accessioned2020-10-21T12:55:30Z
dc.date.available2020-10-21T12:55:30Z
dc.date.created2020-10-09
dc.identifier.issn2352-3409spa
dc.identifier.otherhttps://www.sciencedirect.com/science/article/pii/S235234092031283X?via%3Dihubspa
dc.identifier.urihttp://hdl.handle.net/20.500.12010/14636
dc.format.extent10 páginasspa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.publisherData in Briefspa
dc.sourcereponame:Expeditio Repositorio Institucional UJTLspa
dc.sourceinstname:Universidad de Bogotá Jorge Tadeo Lozanospa
dc.subjectHydroxychloroquinespa
dc.subjectOpinion miningspa
dc.subjectPolarityspa
dc.subjectSocial mediaspa
dc.subjectStance classificationspa
dc.subjectTwitterspa
dc.titleA stance data set on polarized conversations on Twitter about the efficacy of hydroxychloroquine as a treatment for COVID-19spa
dc.type.localArtículospa
dc.subject.lembSíndrome respiratorio agudo gravespa
dc.subject.lembCOVID-19spa
dc.subject.lembSARS-CoV-2spa
dc.subject.lembCoronavirusspa
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccessspa
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersionspa
dc.rights.localAcceso restringidospa
dc.identifier.doihttps://doi.org/10.1016/j.dib.2020.106401spa
dc.description.abstractenglishAt the time of this study, the SARS-CoV-2 virus that caused the COVID-19 pandemic has spread significantly across the world. Considering the uncertainty about policies, health risks, financial difficulties, etc. the online media, especially the Twitter platform, is experiencing a high volume of activity related to this pandemic. Among the hot topics, the polarized debates about unconfirmed medicines for the treatment and prevention of the disease have attracted significant attention from online media users. In this work, we present a stance data set, COVID-CQ, of user-generated content on Twitter in the context of COVID-19. We investigated more than 14 thousand tweets and manually annotated the tweet initiators’ opinions regarding the use of “chloroquine” and “hydroxychloroquine” for the treatment or prevention of COVID-19. To the best of our knowledge, COVID-CQ is the first data set of Twitter users’ stances in the context of the COVID-19 pandemic, and the largest Twitter data set on users’ stances towards a claim, in any domain. We have made this data set available to the research community via the Mendeley Data repository. We expect this data set to be useful for many research purposes, including stance detection, evolution and dynamics of opinions regarding this outbreak, and changes in opinions in response to the exogenous shocks such as policy decisions and events.spa
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa


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