Bootstrapping polar-opposite emotion dimensions from online reviews

Luwen Huangfu, Mihai Surdeanu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We propose a novel bootstrapping approach for the acquisition of lexicons from unannotated, informal online texts (in our case, Yelp reviews) for polar-opposite emotion dimension values from the Ortony/Clore/Collins model of emotions (e.g., desirable/undesirable). Our approach mitigates the intrinsic problem of limited supervision in bootstrapping with an effective strategy that softly labels unlabeled terms, which are then used to better estimate the quality of extraction patterns. Further, we propose multiple solutions to control for semantic drift by taking advantage of the polarity of the categories to be learned (e.g., praiseworthy vs. blameworthy). Experimental results demonstrate that our algorithm achieves considerably better performance than several baselines.

Original languageEnglish (US)
Title of host publicationLREC 2018 - 11th International Conference on Language Resources and Evaluation
EditorsHitoshi Isahara, Bente Maegaard, Stelios Piperidis, Christopher Cieri, Thierry Declerck, Koiti Hasida, Helene Mazo, Khalid Choukri, Sara Goggi, Joseph Mariani, Asuncion Moreno, Nicoletta Calzolari, Jan Odijk, Takenobu Tokunaga
PublisherEuropean Language Resources Association (ELRA)
Pages613-618
Number of pages6
ISBN (Electronic)9791095546009
StatePublished - 2019
Event11th International Conference on Language Resources and Evaluation, LREC 2018 - Miyazaki, Japan
Duration: May 7 2018May 12 2018

Publication series

NameLREC 2018 - 11th International Conference on Language Resources and Evaluation

Other

Other11th International Conference on Language Resources and Evaluation, LREC 2018
Country/TerritoryJapan
CityMiyazaki
Period5/7/185/12/18

Keywords

  • Bootstrapping
  • Limited supervision
  • Semantic drift

ASJC Scopus subject areas

  • Linguistics and Language
  • Education
  • Library and Information Sciences
  • Language and Linguistics

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