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dc.contributor.authorBeck, Tilman
dc.contributor.authorLee, Ji-Ung
dc.contributor.authorViehmann, Christina
dc.contributor.authorMaurer, Marcus
dc.contributor.authorQuiring, Oliver
dc.contributor.authorGurevych, Iryna
dc.date.accessioned2021-05-31T11:08:22Z
dc.date.available2021-05-31T11:08:22Z
dc.date.issued2021-08
dc.identifier.urihttps://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2780
dc.descriptionThe UKP Covid-19 Twitter Corpus includes 2,785 tweets annotated by student annotators and 200 expert-annotated tweets in German. Each tweet was annotated as either a supporting opinion ("Support"), an attacking argument ("Refute"), a commenting statement ("Comment") or unrelated ("Unrelated") with respect to governmental measures taken to prevent the spread of Covid-19.en_US
dc.language.isodeen_US
dc.relationIsCitedBy;URL;https://arxiv.org/abs/2105.12980
dc.rightsCreative Commons Attribution 4.0
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectNLPen_US
dc.subjectOpinion Miningen_US
dc.subjectSocial Mediaen_US
dc.subjectCovid-19en_US
dc.subject.classification409-06 Informationssysteme, Prozess- und Wissensmanagementen_US
dc.subject.ddc004
dc.titleOpinion Mining Corpus on German Tweets about the Covid-19 Pandemicen_US
dc.typeDataseten_US
dc.typeTexten_US
dc.typeSoftwareen_US
tud.projectDFG | GRK2222 | TP Gurevychen_US
tud.projectEU/EFRE | 20005482 | TexPrax - Gurevychen_US
tud.unitTUDa


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Creative Commons Attribution 4.0
Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0