Reference : An Annotation Framework for Luxembourgish Sentiment Analysis

	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science Arts & humanities : Languages & linguistics
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/43136

Title :	An Annotation Framework for Luxembourgish Sentiment Analysis
Language :	English
Author, co-author :	Sirajzade, Joshgun [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
	Gierschek, Daniela [University of Luxembourg > Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) > Identités, Politiques, Sociétés, Espaces (IPSE) >]
	Schommer, Christoph [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Publication date :	May-2020
Main document title :	Proceedings of the LREC 2020 1st Joint SLTU and CCURL Workshop (SLTU-CCURL 2020)
Editor :	Besacier, Laurent
	Sakti, Sakriani
	Soria, Claudia
	Beermann, Dorothee
Publisher :	European Language Resources Association (ELRA)
Pages :	172-176
Peer reviewed :	Yes
Audience :	International
ISBN :	979-10-95546-35-1
	9791095546351
City :	Paris
Country :	France
Event name :	LREC 2020 Workshop Language Resources and Evaluation Conference 11–16 May 2020, 1st Joint SLTU and CCURL Workshop (SLTU-CCURL 2020)
Event date :	from 11-05-2020 to 16-05-2020
Event organizer :	European Language Resources Association (ELRA)
Event place (city) :	Marseille
Event country :	France
Keywords :	[en] Opinion Mining ; Sentiment Analysis ; Corpus (Creation, Annotation, etc.) ; Luxembourgish Language ; Crowdsourcing ; Time Series
Abstract :	[en] The aim of this paper is to present a framework developed for crowdsourcing sentiment annotation for the low-resource language Luxembourgish. Our tool is easily accessible through a web interface and facilitates sentence-level annotation of several annotators in parallel. In the heart of our framework is an XML database, which serves as central part linking several components. The corpus in the database consists of news articles and user comments. One of the components is LuNa, a tool for linguistic preprocessing of the data set. It tokenizes the text, splits it into sentences and assigns POS-tags to the tokens. After that, the preprocessed text is stored in XML format into the database. The Sentiment Annotation Tool, which is a browser-based tool, then enables the annotation of split sentences from the database. The Sentiment Engine, a separate module, is trained with this material in order to annotate the whole data set and analyze the sentiment of the comments over time and in relationship to the news articles. The gained knowledge can again be used to improve the sentiment classification on the one hand and on the other hand to understand the sentiment phenomenon from the linguistic point of view.
Target :	Researchers ; Professionals ; Students ; General public
Permalink :	http://hdl.handle.net/10993/43136
Other URL :	https://lrec2020.lrec-conf.org/media/proceedings/Workshops/Books/SLTUCCURLbook.pdf

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	Fulltext file(s): File Commentary Version Size Access Open access AnAnnotationFrameworkforLuxembourgishSentimentAnalysis.pdf Publisher postprint 1.15 MB View/Open

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