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dc.contributor.authorBravo-Marquez, Felipeen_NZ
dc.contributor.authorFrank, Eibeen_NZ
dc.contributor.authorPfahringer, Bernharden_NZ
dc.contributor.editorYang, Qen_NZ
dc.contributor.editorWooldridge, Men_NZ
dc.coverage.spatialBuenos Aires, Argentinaen_NZ
dc.date.accessioned2015-09-08T21:37:10Z
dc.date.available2015en_NZ
dc.date.available2015-09-08T21:37:10Z
dc.date.issued2015en_NZ
dc.identifier.citationBravo-Márquez, F., Frank, E., & Pfahringer, B. (2015). Positive, Negative, or Neutral: Learning an Expanded Opinion Lexicon from Emoticon-annotated Tweets. In Q. Yang & M. Wooldridge (Eds.), Proc 24th International Joint Conference on Artificial Intelligence (pp. 1229–1235). Buenos Aires, Argentina: AAAI Press.en
dc.identifier.urihttps://hdl.handle.net/10289/9630
dc.description.abstractWe present a supervised framework for expanding an opinion lexicon for tweets. The lexicon contains part-of-speech (POS) disambiguated entries with a three-dimensional probability distribution for positive, negative, and neutral polarities. To obtain this distribution using machine learning, we propose word-level attributes based on POS tags and information calculated from streams of emoticon annotated tweets. Our experimental results show that our method outperforms the three-dimensional word-level polarity classification performance obtained by semantic orientation, a state-of-the-art measure for establishing world-level sentiment.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherAAAI Pressen_NZ
dc.relation.urihttp://ijcai.org/papers15/contents.phpen_NZ
dc.rightsThis is an author's accepted version of a paper published in the Proceedings of the 24th International Joint Conference on Artificial Intelligence. © 2015 International Joint Conferences on Artificial Intelligence.
dc.sourceIJCAI 2015en_NZ
dc.subjectMachine learning
dc.titlePositive, Negative, or Neutral: Learning an Expanded Opinion Lexicon from Emoticon-annotated Tweetsen_NZ
dc.typeConference Contribution
dc.relation.isPartOfProc 24th International Joint Conference on Artificial Intelligenceen_NZ
pubs.begin-page1229
pubs.elements-id128084
pubs.end-page1235
pubs.finish-date2015-07-31en_NZ
pubs.start-date2015-07-25en_NZ
pubs.volume2015-Januaryen_NZ


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