Manually sentiment annotated Slovenian news corpus SentiNews 1.0

PID

Between 2 and 6 annotators independently sentiment annotated a stratified random sample of 10,427 documents from the Slovenian news portals 24ur, Dnevnik, Finance, Rtvslo, and Žurnal24. These portals contain political, business, economic and financial content. The texts were annotated using the five-level Lickert scale (1 – very negative, 2 – negative, 3 – neutral, 4 – positive, and 5 – very positive) on three levels of granularity, i.e. on the document, paragraph, and sentence level.

Identifier
PID http://hdl.handle.net/11356/1110
Related Identifier https://doi.org/10.1007/s10579-018-9413-3
Related Identifier https://github.com/19Joey85/Sentiment-annotated-news-corpus-and-sentiment-lexicon-in-Slovene/
Metadata Access http://www.clarin.si/repository/oai/request?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:www.clarin.si:11356/1110
Provenance
Creator Bučar, Jože
Publisher Faculty of Information Studies Novo mesto
Publication Year 2017
Rights Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0); https://creativecommons.org/licenses/by-sa/4.0/; PUB
OpenAccess true
Contact info(at)clarin.si
Representation
Language Slovenian; Slovene
Resource Type corpus
Format text/plain; application/pdf; text/plain; charset=utf-8; downloadable_files_count: 5
Discipline Linguistics