Opinion Mining Corpus on German Tweets about the Covid-19 Pandemic

The 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.

Identifier
Source https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2780
Related Identifier https://arxiv.org/abs/2105.12980
Metadata Access https://tudatalib.ulb.tu-darmstadt.de/oai/openairedata?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:tudatalib.ulb.tu-darmstadt.de:tudatalib/2780
Provenance
Creator Beck, Tilman; Lee, Ji-Ung; Viehmann, Christina; Maurer, Marcus; Quiring, Oliver; Gurevych, Iryna
Publisher TU Darmstadt
Contributor Deutsche Forschungsgemeinschaft; TU Darmstadt
Publication Year 2021
Funding Reference Deutsche Forschungsgemeinschaft info:eu-repo/grantAgreement/DFG/GRK2222/TPGurevych
Rights Creative Commons Attribution 4.0; info:eu-repo/semantics/openAccess
OpenAccess true
Contact https://tudatalib.ulb.tu-darmstadt.de/page/contact
Representation
Language German
Resource Type Dataset
Format application/zip
Discipline Other