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International Conference on Neural Information Processing

ICONIP 2021: Neural Information Processing pp 526–536Cite as

Isn’t It Ironic, Don’t You Think?

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 13111))

Abstract

Currently, dealing with figurative language, such as irony, is one of the challenging and interesting problems in natural language processing. Because irony is so widespread in user-created content (UCC) such as social media posts, its prevalence makes it technically challenging to determine sentiments or interpret opinions. Investigating irony content is an essential problem which can be extended and leveraged for other tasks such as sentiment and opinion mining. The present work proposes a Hierarchical Attention based Neural network for identifying ironic tweets. Our method exploits the structure and semantic features like POS tagging and sentiment flow shifts. We then present our results on the Task 3 of the Semantic Evaluation 2018 workshop named “Irony Detection in English Tweets” dataset. Furthermore, we perform a comprehensive analysis over the generated results, shedding insights on future research for the irony detection task.

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Notes

  1. 1.

    http://www.nltk.org/howto/sentiment.html.

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Author information

Authors and Affiliations

  1. University of Texas at Dallas, Richardson, USA

    Saichethan Miriyala Reddy

  2. BITS Pilani, Goa Campus, Goa, India

    Swati Agarwal

Authors
  1. Saichethan Miriyala Reddy
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  2. Swati Agarwal
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Corresponding author

Correspondence to Swati Agarwal .

Editor information

Editors and Affiliations

  1. Sampoerna University, Jakarta, Indonesia

    Teddy Mantoro

  2. Kyungpook National University, Daegu, Korea (Republic of)

    Minho Lee

  3. Sampoerna University, Jakarta, Indonesia

    Media Anugerah Ayu

  4. Murdoch University, Murdoch, WA, Australia

    Kok Wai Wong

  5. Universitas Indonesia, Depok, Indonesia

    Achmad Nizar Hidayanto

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Reddy, S.M., Agarwal, S. (2021). Isn’t It Ironic, Don’t You Think?. In: Mantoro, T., Lee, M., Ayu, M.A., Wong, K.W., Hidayanto, A.N. (eds) Neural Information Processing. ICONIP 2021. Lecture Notes in Computer Science(), vol 13111. Springer, Cham. https://doi.org/10.1007/978-3-030-92273-3_43

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  • DOI: https://doi.org/10.1007/978-3-030-92273-3_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-92272-6

  • Online ISBN: 978-3-030-92273-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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