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Exploring the Role of Gender in 19th Century Fiction Through the Lens of Word Embeddings

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Language, Data, and Knowledge (LDK 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10318))

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Abstract

Within the last decade, substantial advances have been made in the field of computational linguistics, due in part to the evolution of word embedding algorithms inspired by neural network models. These algorithms attempt to derive a set of vectors which represent the vocabulary of a textual corpus in a new embedded space. This new representation can then be used to measure the underlying similarity between words. In this paper, we explore the role an author’s gender may play in the selection of words that they choose to construct their narratives. Using a curated corpus of forty-eight 19th century novels, we generate, visualise, and investigate word embedding representations using a list of gender-encoded words. This allows us to explore the different ways in which male and female authors of this corpus use terms relating to contemporary understandings of gender and gender roles.

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Notes

  1. 1.

    http://ryanheuser.org/word-vectors-1.

  2. 2.

    http://www.ghostweather.com/files/word2vecpride.

  3. 3.

    The annotated texts were created as part of the “Nation, Gender, Genre��� project. See http://www.nggprojectucd.ie.

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Acknowledgments

This research was partly supported by Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289, in collaboration with the Nation, Genre and Gender project funded by the Irish Research Council.

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Authors and Affiliations

  1. School of Computer Science, University College Dublin, Dublin, Ireland

    Siobhán Grayson & Derek Greene

  2. Humanities Institute, University College Dublin, Dublin, Ireland

    Maria Mulvany, Karen Wade & Gerardine Meaney

Authors
  1. Siobhán Grayson
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  2. Maria Mulvany
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  3. Karen Wade
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  4. Gerardine Meaney
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  5. Derek Greene
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Corresponding author

Correspondence to Siobhán Grayson .

Editor information

Editors and Affiliations

  1. Universidad Politécnica de Madrid, Madrid, Spain

    Jorge Gracia

  2. Nanyang Technological University, Singapore, Singapore

    Francis Bond

  3. Insight Centre for Data Analytics, National University of Ireland, Galway, Galway, Ireland

    John P. McCrae

  4. Insight Centre for Data Analytics, National University of Ireland, Galway, Ireland

    Paul Buitelaar

  5. Goethe-University Frankfurt, Frankfurt, Germany

    Christian Chiarcos

  6. University of Leipzig, Leipzig, Germany

    Sebastian Hellmann

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Grayson, S., Mulvany, M., Wade, K., Meaney, G., Greene, D. (2017). Exploring the Role of Gender in 19th Century Fiction Through the Lens of Word Embeddings. In: Gracia, J., Bond, F., McCrae, J., Buitelaar, P., Chiarcos, C., Hellmann, S. (eds) Language, Data, and Knowledge. LDK 2017. Lecture Notes in Computer Science(), vol 10318. Springer, Cham. https://doi.org/10.1007/978-3-319-59888-8_30

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  • DOI: https://doi.org/10.1007/978-3-319-59888-8_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59887-1

  • Online ISBN: 978-3-319-59888-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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