Aspect-Based Sentiment Analysis as a Multi-Label Classification Task on the Domain of German Hotel Reviews

URN to cite this document:: urn:nbn:de:bvb:355-epub-582615

Fehle, Jakob ; Münster, Leonie ; Schmidt, Thomas

; Wolff, Christian

License: Creative Commons Attribution 4.0
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Date of publication of this fulltext: 25 Jun 2024 06:47

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Item type:	Book section
ISBN:	979-8-89176-029-5
Open Access Type:	CC-License
Title of Book:	Proceedings of the 19th Conference on Natural Language Processing (KONVENS 2023)
Publisher:	The Association for Computational Linguistics
Place of Publication:	Stroudsburg, PA
Page Range:	pp. 202-218
Date:	2023
Institutions:	Languages and Literatures > Institut für Information und Medien, Sprache und Kultur (I:IMSK) > Lehrstuhl für Medieninformatik (Prof. Dr. Christian Wolff) Informatics and Data Science > Department Human-Centered Computing > Lehrstuhl für Medieninformatik (Prof. Dr. Christian Wolff)
Keywords:	sentiment analysis, hotel reviews, aspect-based, multi-label, annotation, corpus
Dewey Decimal Classification:	000 Computer science, information & general works > 004 Computer science
Status:	Published
Refereed:	Yes, this version has been refereed
Created at the University of Regensburg:	Yes
Item ID:	58261

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Abstract

Aspect-Based Sentiment Analysis (ABSA) plays a crucial role in understanding finegrained customer feedback, particularly in domains like hospitality where specific aspects of service often influence overall satisfaction. However, non-English languages such as German face a scarcity of readily available corpora and evaluated methods for ABSA, making it a challenging problem. This paper addresses ...