@article{beigman-klebanov-etal-2013-using,
    title = "Using Pivot-Based Paraphrasing and Sentiment Profiles to Improve a Subjectivity Lexicon for Essay Data",
    author = "Beigman Klebanov, Beata  and
      Madnani, Nitin  and
      Burstein, Jill",
    editor = "Lin, Dekang  and
      Collins, Michael",
    journal = "Transactions of the Association for Computational Linguistics",
    volume = "1",
    year = "2013",
    address = "Cambridge, MA",
    publisher = "MIT Press",
    url = "https://preview.aclanthology.org/fix-sig-urls/Q13-1009/",
    doi = "10.1162/tacl_a_00213",
    pages = "99--110",
    abstract = "We demonstrate a method of improving a seed sentiment lexicon developed on essay data by using a pivot-based paraphrasing system for lexical expansion coupled with sentiment profile enrichment using crowdsourcing. Profile enrichment alone yields up to 15{\%} improvement in the accuracy of the seed lexicon on 3-way sentence-level sentiment polarity classification of essay data. Using lexical expansion in addition to sentiment profiles provides a further 7{\%} improvement in performance. Additional experiments show that the proposed method is also effective with other subjectivity lexicons and in a different domain of application (product reviews)."
}