The Texts:

The seven novels used in this study were downloaded as plain text files in UTF-8 format from Project Gutenberg. These novels are arranged in sets according to specific criteria below. 

Set 1 —  includes three novels considered by Gilbert and Gubar in their book:

  1. Austen, Jane. Sense and Sensibility. 1811. Project Gutenberg ebook, June 1994. https://www.gutenberg.org/cache/epub/161/pg161-images.html.
  2. Brontë, Charlotte. Jane Eyre. 1847. Service & Paton, 1897. Project Gutenberg ebook, March, 1998. https://www.gutenberg.org/cache/epub/1260/pg1260-images.html.
  3. Brontë, Emily. Wuthering Heights. 1847. Project Gutenberg ebook, December, 1996. https://www.gutenberg.org/cache/epub/768/pg768-images.html.

Set 2 —  two novels by female writers contemporary with the Brontë sisters and Jane Austen and not present in Gilbert and Gubar:

  1. Braddon, Mary Elizabeth. Lady Audley’s Secret. 1862. William Tinsley, 1862. Project Gutenberg ebook ,2012. https://www.gutenberg.org/cache/epub/8954/pg8954-images.html.
  2. Ferrier, Susan. Marriage. 1818. Richard Bentley & Son, 1881. Project Gutenberg ebook, 2004. https://www.gutenberg.org/cache/epub/12669/pg12669.html.

Set 3 — one novel written by a male contemporary, the analysis of which may reveal how male writers present their themes and how female writers may mimic masculine styles:

  1. Dickens, Charles. A Tale of Two Cities. 1859. Chapman & Hall, 1859. Project Gutenberg ebook, 1994. https://www.gutenberg.org/cache/epub/98/pg98-images.html.

The Methods:

Through text-mining, I sought to find the frequency in which the keywords I chose appear in my dataset, and then analyze the collocated words as possible sites of hidden meaning. For inspiration, I looked to similar projects such as that of Kenton Ramsby’s, who used texting mining to analyze the short works of Zora Neale Hurston and Richard Wright. In his work, Rambsy defines text-mining as “the process of structuring the input text, deriving patterns within the structured data, and finally evaluating and interpreting the output” (Rambsy 251). Ramsby’s project uses Voyant, but I chose AntConc. AntConc is a toolkit downloadable onto any desktop or laptop computer; it specializes in concordancing and text analysis. For my project, I used its Concordance Tool. This tool derives a list of words present in any given text, as well as the immediate context surrounding them. 

You can manipulate the Concordance Tool to show you a specific amount of surrounding words. To do so, you insert the amount of characters you want to appear in the window. I set it to show 70 characters surrounding the chosen word. Here is a brief video of what this process looks like. 

Figure 1: This video shows how I used the AntConc concordance tool.

As aforementioned, my goal was to use this tool to study specific keywords that may help flag potential hidden themes for Victorian readers that modern readers might miss. I chose words that referred to the characterization of females as having mad tendencies, fierce independence, and/or strong personalities. I chose the words “mad” and “independent” to represent this theme. Gilbert and Gubar also note that many women writers concealed the mental claustrophobia inflicted by the patriarchy within physical descriptions of confined spaces, so I added the word “space.” Here is the final list:

1.     Mad 

2.     Space 

3.     Independent

In order for me to produce an analysis sufficient in supporting Gilbert and Gubar’s work as well as the efficacy of my methods on other novels, I would have to prove that by using data processes I could understand the usage and significance of certain keywords as they pertain to the quest for independence. 

Continue to Results and Analyses.

Return to Main Menu.