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dc.contributor.authorDoan, Tu My
dc.contributor.authorBaumgartner, David
dc.contributor.authorKille, Benjamin Uwe
dc.contributor.authorGulla, Jon Atle
dc.date.accessioned2024-04-24T08:21:46Z
dc.date.available2024-04-24T08:21:46Z
dc.date.created2024-04-16T22:13:15Z
dc.date.issued2024
dc.identifier.issn0302-9743
dc.identifier.urihttps://hdl.handle.net/11250/3127867
dc.description.abstractWe introduce three resources to support research on political texts in Scandinavia. The encoder-decoder transformer models sp-t5 and sp-t5-keyword were trained on political texts. The nor-pvi (available at https://tinyurl.com/nor-pvi) data set comprises political viewpoints, stances, and summaries for Norwegian. Experiments with four distinct tasks show that large-scale models, such as nort5 perform slightly better. Still, sp-t5 and sp-t5-keyword perform almost on par and require much less data and computation.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.titleAutomatically Detecting Political Viewpoints in Norwegian Texten_US
dc.title.alternativeAutomatically Detecting Political Viewpoints in Norwegian Texten_US
dc.typeJournal articleen_US
dc.description.versionsubmittedVersionen_US
dc.source.journalLecture Notes in Computer Science (LNCS)en_US
dc.identifier.doi10.1007/978-3-031-58547-0_20
dc.identifier.cristin2262179
cristin.ispublishedtrue
cristin.fulltextpreprint
cristin.qualitycode1


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