Using Word2Vec to Measure the Positive Sentiment Towards the Term “Queer” in Virginia Woolf

Shin, Heejoung

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https://hdl.handle.net/2142/117109 Copy

Description

Title

Using Word2Vec to Measure the Positive Sentiment Towards the Term “Queer” in Virginia Woolf

Author(s)

Shin, Heejoung

Issue Date

2022-12-22

Keyword(s)

• Virginia Woolf
• queer
• modernism
• sentiment analysis
• word embedding model
• Word2Vec
• NLP

Abstract

This article validates the thesis that Virginia Woolf’s usage of the term “queer” is positive, and that the author is more progressive with her idea of things conceived as “queer” in the era characterized as literary Modernism and in English fiction as a whole from 1850s to 1990s. Using Word2Vec, a word embedding model, I locate the top 100 words semantically closest to “queer” in Woolf’s works and in the works of other modernist authors, James Joyce, F. Scott Fitzgerald, D. H. Lawrence, Gertrude Stein, and Katherine Mansfield. I then measure the net positivity of each author’s list and compare Woolf’s with the individual authors’, and then with words closest to “queer” in English fiction from 1850 to 2000. In demonstrating the usefulness of applying word embedding models in literary criticism, a field that has traditionally primarily relied on interpretation, this article aims to serve as a case study of how a computational approach can benefit close reading.

Publisher

Universitäts- und Landesbibliothek Darmstadt

Has Part

• https://doi.org/10.48694/jcls.106
• https://github.com/heejoungs/woolf_queer

Series/Report Name or Number

Journal of Computational Literary Studies, Volume 1, Issue 1

Type of Resource

text

Language

en

Copyright and License Information

CC BY 4.0

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