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Sentiment composition of words with opposing polarities

Par Conseil national de recherches du Canada

DOITrouver le DOI : https://doi.org/10.18653/v1/N16-1128
AuteurRechercher : 1; Rechercher : 1
Affiliation
  1. Conseil national de recherches du Canada. Technologies de l'information et des communications
FormatTexte, Article
Conférence2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, June 2016, San Diego, California, USA
Résumé
In this paper, we explore sentiment composition in phrases that have at least one positive and at least one negative word—phrases like happy accident and best winter break. We compiled a dataset of such opposing polarity phrases and manually annotated them with real-valued scores of sentiment association. Using this dataset, we analyze the linguistic patterns present in opposing polarity phrases. Finally, we apply several unsupervised and supervised techniques of sentiment composition to determine their efficacy on this dataset. Our best system, which incorporates information from the phrase’s constituents, their parts of speech, their sentiment association scores, and their embedding vectors, obtains an accuracy of over 80% on the opposing polarity phrases.
Date de publication
Maison d’éditionAssociation for Computational Linguistics
Dans
  • Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies : 1102–1108.
Langueanglais
Publications évaluées par des pairsOui
Numéro NPARC23001910
Exporter la noticeExporter en format RIS
Signaler une correctionSignaler une correction (s'ouvre dans un nouvel onglet)
Identificateur de l’enregistrement94d1e786-a373-44e9-b816-b75e2c157f59
Enregistrement créé2017-05-24
Enregistrement modifié2020-03-16
Date de modification :