Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/5122
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dc.contributor.authorDemiröz, Gülşen-
dc.contributor.authorYanıkoğlu, Berrin-
dc.contributor.authorTapucu, Dilek-
dc.contributor.authorSaygın, Yücel-
dc.date.accessioned2017-03-22T08:38:25Z-
dc.date.available2017-03-22T08:38:25Z-
dc.date.issued2012-
dc.identifier.citationDemiröz, G., Yanıkoğlu, B., Tapucu, D., and Saygın, Y. (2012, December 10). Learning domain-specific polarity lexicons. Paper presented at the 12th IEEE International Conference on Data Mining Workshops, ICDMW 2012. doi:10.1109/ICDMW.2012.120en_US
dc.identifier.isbn9780769549255-
dc.identifier.urihttp://doi.org/10.1109/ICDMW.2012.120-
dc.identifier.urihttp://hdl.handle.net/11147/5122-
dc.description12th IEEE International Conference on Data Mining Workshops, ICDMW 2012; Brussels; Belgium; 10 December 2012en_US
dc.description.abstractSentiment analysis aims to automatically estimate the sentiment in a given text as positive or negative. Polarity lexicons, often used in sentiment analysis, indicate how positive or negative each term in the lexicon is. However, since creating domain-specific polarity lexicons is expensive and time-consuming, researchers often use a general purpose or domain-independent lexicon. In this work, we address the problem of adapting a general purpose polarity lexicon to a specific domain and propose a simple yet effective adaptation algorithm. We experimented with two sets of reviews from the hotel and movie domains and observed that while our adaptation techniques changed the polarity values for only a small set of words, the overall test accuracy increased significantly: 77% to 83% in the hotel dataset and 61% to 66% in the movie dataset. © 2012 IEEE.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof12th IEEE International Conference on Data Mining Workshops, ICDMW 2012en_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectLexicon adaptationen_US
dc.subjectMachine learningen_US
dc.subjectNatural language processingen_US
dc.subjectPolarity detectionen_US
dc.subjectSentiment analysisen_US
dc.titleLearning domain-specific polarity lexiconsen_US
dc.typeConference Objecten_US
dc.institutionauthorTapucu, Dilek-
dc.departmentİzmir Institute of Technology. Computer Engineeringen_US
dc.identifier.startpage674en_US
dc.identifier.endpage679en_US
dc.identifier.wosWOS:000320946500089en_US
dc.identifier.scopus2-s2.0-84873156035en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1109/ICDMW.2012.120-
dc.relation.doi10.1109/ICDMW.2012.120en_US
dc.coverage.doi10.1109/ICDMW.2012.120en_US
item.openairetypeConference Object-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextopen-
item.fulltextWith Fulltext-
item.languageiso639-1en-
item.cerifentitytypePublications-
crisitem.author.dept03.04. Department of Computer Engineering-
Appears in Collections:Computer Engineering / Bilgisayar Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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