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A Comparison of Algorithms for Detection of “Figurativeness” in Metaphor, Irony and Puns

  • Conference paper
  • First Online:
Analysis of Images, Social Networks and Texts (AIST 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11832))

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Abstract

Figurative speech is an umbrella term for metaphor, irony, sarcasm, puns and some other speech genres and figures of speech. In research and competitions like SemEval, each of them is usually processed separately with a task-specific model. However, being altogether called “figurative speech”, they should share some property: “figurativeness”. If such a property exists, figurative speech can be processed simultaneously by one and the same algorithm. The present research compares performance of several NLP methods that were designed to detect one type of figurative speech (either metaphor, or irony, or puns) on short texts containing a combination of these types. The study shows that, despite being task-specific, state-of-the-art algorithms are able to process different types of figurative speech fairly well, and some of them are good even at cross-detection when the training set contains one type and the test set another.

The reported study was funded by RFBR according to the research project No. 18-37-00272.

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Notes

  1. 1.

    Only sentences with metaphoricity index over 0.7.

  2. 2.

    The full list of sources is available at https://github.com/evrog/FS_Datasets_AIST_2019.

  3. 3.

    Hyperparameters for CNN: \(d=100, h_1=h_2=7, k_1=k_2=40\). Hyperparameters for RNN: \(d=50, n=20, \epsilon =0.1\). The scripts for NNs are available at https://github.com/evrog/Incongruity.

  4. 4.

    A=accuracy.

  5. 5.

    We do not know of any other systems that use Roget’s Thesaurus in detection of figurative speech.

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Author information

Authors and Affiliations

  1. University of Tyumen, Tyumen, Russia

    Elena Mikhalkova, Nadezhda Ganzherli & Anna Glazkova

  2. University of Gothenburg, Gothenburg, Sweden

    Vladislav Maraev

  3. OOO ITSK, Tyumen, Russia

    Dmitriy Grigoriev

Authors
  1. Elena Mikhalkova
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  2. Nadezhda Ganzherli
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  3. Vladislav Maraev
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  4. Anna Glazkova
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  5. Dmitriy Grigoriev
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Corresponding author

Correspondence to Elena Mikhalkova .

Editor information

Editors and Affiliations

  1. RWTH Aachen University, Aachen, Germany

    Wil M. P. van der Aalst

  2. University of Ljubljana, Ljubljana, Slovenia

    Vladimir Batagelj

  3. National Research University Higher School of Economics, Moscow, Russia

    Dmitry I. Ignatov

  4. Krasovskii Institute of Mathematics and Mechanics, Yekaterinburg, Russia

    Michael Khachay

  5. National Research University Higher School of Economics, Moscow, Russia

    Valentina Kuskova

  6. University of Oslo, Oslo, Norway

    Andrey Kutuzov

  7. National Research University Higher School of Economics, Moscow, Russia

    Sergei O. Kuznetsov

  8. National Research University Higher School of Economics, Moscow, Russia

    Irina A. Lomazova

  9. Lomonosov Moscow State University, Moscow, Russia

    Natalia Loukachevitch

  10. LORIA, Vandœuvre-lès-Nancy, France

    Amedeo Napoli

  11. University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

  12. Ca Foscari University of Venice, Venice, Italy

    Marcello Pelillo

  13. National Research University Higher School of Economics, Nizhny Novgorod, Russia

    Andrey V. Savchenko

  14. Kazan Federal University, Kazan, Russia

    Elena Tutubalina

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Mikhalkova, E., Ganzherli, N., Maraev, V., Glazkova, A., Grigoriev, D. (2019). A Comparison of Algorithms for Detection of “Figurativeness” in Metaphor, Irony and Puns. In: van der Aalst, W., et al. Analysis of Images, Social Networks and Texts. AIST 2019. Lecture Notes in Computer Science(), vol 11832. Springer, Cham. https://doi.org/10.1007/978-3-030-37334-4_17

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  • DOI: https://doi.org/10.1007/978-3-030-37334-4_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37333-7

  • Online ISBN: 978-3-030-37334-4

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