Twitter sentiment for 15 European languages

Mozetič, Igor; Grčar, Miha; Smailović, Jasmina

dc.contributor.author	Mozetič, Igor
dc.contributor.author	Grčar, Miha
dc.contributor.author	Smailović, Jasmina
dc.date.accessioned	2016-02-23T10:08:53Z
dc.date.available	2016-04-25T21:45:18Z
dc.date.issued	2016-02-23
dc.identifier.uri	http://hdl.handle.net/11356/1054
dc.description	The dataset contains over 1.6 million tweets (tweet IDs), labeled with sentiment by human annotators. There are 15 Twitter corpora for the corresponding 15 European languages. The data can be used to train and evaluate Twitter sentiment classifiers, to compute annotator agreement, or to study the differences between language usage on Twitter. The data analysis is described in the following papers: I. Mozetič, M. Grčar, J. Smailović. Multilingual Twitter sentiment classification: The role of human annotators, PLoS ONE 11(5): e0155036, doi: 10.1371/journal.pone.e0155036, 2016. (http://dx.doi.org/10.1371/journal.pone.0155036) I. Mozetič, L. Torgo, V. Cerqueira, J. Smailović. How to evaluate sentiment classifiers for Twitter time-ordered data?, PLoS ONE 13(3): e0194317, doi: 10.1371/journal.pone.0194317, 2018. (https://dx.doi.org/10.1371/journal.pone.0194317)
dc.language.iso	sqi
dc.language.iso	bos
dc.language.iso	bul
dc.language.iso	hrv
dc.language.iso	eng
dc.language.iso	deu
dc.language.iso	hun
dc.language.iso	pol
dc.language.iso	por
dc.language.iso	srp
dc.language.iso	rus
dc.language.iso	slk
dc.language.iso	slv
dc.language.iso	spa
dc.language.iso	swe
dc.publisher	Jožef Stefan Institute
dc.relation	info:eu-repo/grantAgreement/EC/FP7/610704
dc.relation	info:eu-repo/grantAgreement/EC/FP7/317532
dc.relation	info:eu-repo/grantAgreement/EC/H2020/640772
dc.relation.isreferencedby	https://dx.doi.org/10.1371/journal.pone.0155036
dc.relation.isreferencedby	https://dx.doi.org/10.1371/journal.pone.0194317
dc.rights	Creative Commons - Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)
dc.rights.uri	https://creativecommons.org/licenses/by-sa/4.0/
dc.rights.label	PUB
dc.subject	sentiment classification
dc.subject	Twitter
dc.subject	inter-annotator agreement
dc.subject	annotator self-agreement
dc.subject	multilingual
dc.title	Twitter sentiment for 15 European languages
dc.type	corpus
metashare.ResourceInfo#ContentInfo.mediaType	text
has.files	yes
branding	CLARIN.SI data & tools
contact.person	Igor Mozetic igor.mozetic@ijs.si Jožef Stefan Institute
sponsor	EC 610704 SIMPOL euFunds info:eu-repo/grantAgreement/EC/FP7/610704
sponsor	EC 317532 MULTIPLEX euFunds info:eu-repo/grantAgreement/EC/FP7/317532
sponsor	EC 640772 DOLFINS euFunds info:eu-repo/grantAgreement/EC/H2020/640772
sponsor	ARRS (Slovenian Research Agency) P2-103 Knowledge Technologies nationalFunds
size.info	1643735 items
files.count	16
files.size	51781021

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There are 15 files for the corresponding 15 European languages:
Albanian, Bosnian, Bulgarian, Croatian, English, German, Hungarian,
Polish, Portuguese, Russian, Serbian, Slovak, Slovenian, Spanish, and Swedish.

Files are in the standard csv format, each line has the following form:
TweetID,HandLabel,AnnotatorID

TweetID is assigned by Twitter and can be used to retreive the tweet.
HandLabel is the sentimen label as assigned by the human annotator
(Negative, Neutral, or Positive).
AnnotatorID is a 3-digit integer assigned to anonymous annotators,
and can be used to identify tweets annotated several times by the
same or by different annotators. . . .