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

  • Siobhán Grayson
  • Maria Mulvany
  • Karen Wade
  • Gerardine Meaney
  • Derek Greene
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10318)

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.

Notes

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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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Siobhán Grayson
    • 1
  • Maria Mulvany
    • 2
  • Karen Wade
    • 2
  • Gerardine Meaney
    • 2
  • Derek Greene
    • 1
  1. 1.School of Computer ScienceUniversity College DublinDublinIreland
  2. 2.Humanities InstituteUniversity College DublinDublinIreland

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