@inproceedings{kesarwani-etal-2017-metaphor,
    title = "Metaphor Detection in a Poetry Corpus",
    author = "Kesarwani, Vaibhav  and
      Inkpen, Diana  and
      Szpakowicz, Stan  and
      Tanasescu, Chris",
    editor = "Alex, Beatrice  and
      Degaetano-Ortlieb, Stefania  and
      Feldman, Anna  and
      Kazantseva, Anna  and
      Reiter, Nils  and
      Szpakowicz, Stan",
    booktitle = "Proceedings of the Joint {SIGHUM} Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W17-2201",
    doi = "10.18653/v1/W17-2201",
    pages = "1--9",
    abstract = "Metaphor is indispensable in poetry. It showcases the poet{'}s creativity, and contributes to the overall emotional pertinence of the poem while honing its specific rhetorical impact. Previous work on metaphor detection relies on either rule-based or statistical models, none of them applied to poetry. Our method focuses on metaphor detection in a poetry corpus. It combines rule-based and statistical models (word embeddings) to develop a new classification system. Our system has achieved a precision of 0.759 and a recall of 0.804 in identifying one type of metaphor in poetry.",
}