Sentiment Annotated Dataset of Croatian News

Name: Sentiment Annotated Dataset of Croatian News
License: https://creativecommons.org/licenses/by-nc-nd/4.0/

Pelicon, Andraž; Pranjić, Marko; Miljković, Dragana; Škrlj, Blaž; Pollak, Senja

dc.contributor.author	Pelicon, Andraž
dc.contributor.author	Pranjić, Marko
dc.contributor.author	Miljković, Dragana
dc.contributor.author	Škrlj, Blaž
dc.contributor.author	Pollak, Senja
dc.date.accessioned	2020-09-24T11:33:35Z
dc.date.available	2020-09-24T11:33:35Z
dc.date.issued	2020-09-15
dc.identifier.uri	http://hdl.handle.net/11356/1342
dc.description	We present a collection of sentiment annotations for news articles (article links) in Croatian language. A set of 2025 news articles was gathered from 24sata, one of the leading media companies in Croatia with the highest circulation. 6 annotators annotated the articles on the document level using a five-level Likert scale (1—very negative, 2—negative, 3—neutral, 4—positive, and 5—very positive). The final sentiment of an instance was defined as the average of the sentiment scores given by the different annotators. An instance was labeled as negative, if the average of given scores was less than or equal to 2.4; neutral, if the average of given scores was between 2.4 and 3.6; or positive, if the average of given scores was greater than or equal to 3.6. The annotation guidelines correspond to the Slovenian sentiment-annotated collection of news SentiNews 1.0 (http://hdl.handle.net/11356/1110). If you use the dataset, please cite the following paper (which contains also the details on the dataset creation, and on monolingual and cross-lingual sentiment classification experiments): Pelicon, A.; Pranjić, M.; Miljković, D.; Škrlj, B.; Pollak, S. Zero-Shot Learning for Cross-Lingual News Sentiment Classification. Appl. Sci. 2020, 10, 5993. https://doi.org/10.3390/app10175993
dc.language.iso	hrv
dc.publisher	Jožef Stefan Institute
dc.relation	info:eu-repo/grantAgreement/EC/H2020/825153
dc.relation.isreferencedby	https://doi.org/10.3390/app10175993
dc.rights	Creative Commons - Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
dc.rights.uri	https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.label	PUB
dc.source.uri	http://embeddia.eu/
dc.subject	news corpus
dc.subject	sentiment classification
dc.subject	manual annotation
dc.title	Sentiment Annotated Dataset of Croatian News
dc.type	corpus
metashare.ResourceInfo#ContentInfo.mediaType	text
has.files	yes
branding	CLARIN.SI data & tools
contact.person	Andraž Pelicon Andraz.Pelicon@ijs.si Jožef Stefan Institute
sponsor	European Union EC/H2020/825153 EMBEDDIA - Cross-Lingual Embeddings for Less-Represented Languages in European News Media euFunds info:eu-repo/grantAgreement/EC/H2020/825153
sponsor	European Union’s Rights,Equality and Citizenship Programme 875263 IMSyPP - Innovative Monitoring Systems and PreventionPolicies of Online Hate Speech Other
sponsor	ARRS (Slovenian Research Agency) P2-103 Knowledge Technologies nationalFunds
size.info	2025 entries
files.count	1
files.size	87652