2026-05-22T00:23:27Zhttp://www.clarin.si/repository/oai/request

oai:www.clarin.si:11356/11102023-03-27T17:01:19Zhdl_11356_1023hdl_11356_1024

Manually sentiment annotated Slovenian news corpus SentiNews 1.0 Bučar, Jože news corpus sentiment classification opinion mining manual annotation 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. 2017-04-29 corpus http://hdl.handle.net/11356/1110 slv https://doi.org/10.1007/s10579-018-9413-3 Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) https://creativecommons.org/licenses/by-sa/4.0/ PUB text/plain text/plain text/plain text/plain application/pdf text/plain; charset=utf-8 downloadable_files_count: 5 Faculty of Information Studies Novo mesto https://github.com/19Joey85/Sentiment-annotated-news-corpus-and-sentiment-lexicon-in-Slovene/