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dc.date.accessioned2022-11-01T17:10:00Z
dc.date.available2022-11-01T17:10:00Z
dc.date.created2022-10-31T12:12:04Z
dc.date.issued2022
dc.identifier.citationRønningstad, Egil Øvrelid, Lilja Velldal, Erik . Entity-Level Sentiment Analysis (ELSA): An Exploratory Task Survey. Proceedings of the 29th International Conference on Computational Linguistics. 2022, 6773-6783
dc.identifier.urihttp://hdl.handle.net/10852/97460
dc.description.abstractThis paper explores the task of identifying the overall sentiment expressed towards volitional entities (persons and organizations) in a document - what we refer to as Entity-Level Sentiment Analysis (ELSA). While identifying sentiment conveyed towards an entity is well researched for shorter texts like tweets, we find little to no research on this specific task for longer texts with multiple mentions and opinions towards the same entity. This lack of research would be understandable if ELSA can be derived from existing tasks and models. To assess this, we annotate a set of professional reviews for their overall sentiment towards each volitional entity in the text. We sample from data already annotated for document-level, sentence-level, and target-level sentiment in a multi-domain review corpus, and our results indicate that there is no single proxy task that provides this overall sentiment we seek for the entities at a satisfactory level of performance. We present a suite of experiments aiming to assess the contribution towards ELSA provided by document-, sentence-, and target-level sentiment analysis, and provide a discussion of their shortcomings. We show that sentiment in our dataset is expressed not only with an entity mention as target, but also towards targets with a sentiment-relevant relation to a volitional entity. In our data, these relations extend beyond anaphoric coreference resolution, and our findings call for further research of the topic. Finally, we also present a survey of previous relevant work.
dc.description.abstractEntity-Level Sentiment Analysis (ELSA): An Exploratory Task Survey
dc.languageEN
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleEntity-Level Sentiment Analysis (ELSA): An Exploratory Task Survey
dc.title.alternativeENEngelskEnglishEntity-Level Sentiment Analysis (ELSA): An Exploratory Task Survey
dc.typeJournal article
dc.creator.authorRønningstad, Egil
dc.creator.authorØvrelid, Lilja
dc.creator.authorVelldal, Erik
cristin.unitcode185,15,5,48
cristin.unitnameSpråkteknologigruppen
cristin.ispublishedtrue
cristin.fulltextoriginal
dc.identifier.cristin2066720
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Proceedings of the 29th International Conference on Computational Linguistics&rft.volume=&rft.spage=6773&rft.date=2022
dc.identifier.jtitleProceedings of the 29th International Conference on Computational Linguistics
dc.identifier.startpage6773
dc.identifier.endpage6783
dc.subject.nviVDP::Informasjons- og kommunikasjonsteknologi: 550
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn2951-2093
dc.type.versionPublishedVersion
dc.relation.projectNFR/309834
dc.relation.projectNFR/270908


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