Text processing tools such as Voyant enhance our ability to recognize and find meaning in language patterns within a body of text beyond what can be done with a close reading only. Looking at the information generated about the use of certain words and where they occur adds to our own interpretation by offering a bird’s-eye view to a body of text. Challenges are encountered, however, when the information generated is interpreted on its own without having read the work because there are nuanced meanings to any one word depending on the context in which it is used.

One problem with computers is their inability to group semantically related terms. While we have no difficulty grouping words like swim, swimmer, and swimming, a computer cannot do this without being explicitly told the words are related. While trying to look at pronoun occurrences, it would have been helpful if we could easily group them by gender. If there were an easy way to group he, him, and his, our search would have been greatly expedited. Likewise, the words “like” and “love,” which can both have various meanings, sometimes may mean the same thing, but the computer cannot pick up on this.

Nevertheless, we found that the pronoun “I” was mentioned over 300 times in The World’s Wife. In TWW I was able to include the pronoun “I” under the confirmed assumption that in at least 95% of all cases, it will refer to a woman, as the speakers are all feminine. According to my count, men use the word “I” in only four poems where they have dialogue: once in “from Mrs Tiresias,” 5 times in “Mrs Faust,” 5 times in “Delilah,” and once in “Anne Hathaway”–of a total of 322 occurrences of “I”. It would be enlightening to find a way to differentiate the gender of “I” in SFN. In Standing Female Nude, “she” and “her” were the most used pronouns. This is reflective in the literature because The World’s Wife is mainly written about a woman’s experiences while Standing Female Nude is more broad and is about multiple perspectives and relationships. While digitally searching through the text, it becomes clear that the two books are about different subjects.

A similar problem with searching through the text digitally, is that computers can’t infer what’s happening in the poetry. Duffy can create an air of sadness without ever using the word sad. The nature of Duffy’s work requires a close reading of the text to extract meaning and emotion, something that the computer is unable to do. It is necessary to apply textual interpretation to the information found by the computer in order to extract meaningful information. In the graphic showing the tool “Document Terms,” direct names of emotions such as “shame” and “sadness” have some of the least occurrences, while more vague terms such as “laugh” and “tears” occur more showing that Duffy uses poetic language to show emotions and expects us to infer these emotions, but the computer cannot do this by itself.

In examining emotions found throughout the text, the analysis tool “Trends” can also display a graph of incidences of emotive terms found over the course of the document, but occasionally the graph does show a curve when no incidence of the term has occurred. Because of this, the “Document Terms” tool appears to have more integrity in displaying incidences of emotive words. This tool can show the terms in a broad view that might be more time-intensive and prone to human error should one search the book for these terms manually.

The TextualArc is an interesting tool. It is a large oval with the entire text around the edges. Each term that appears more than once in the corpus is plotted somewhere in the oval, with each occurrence ‘pulling’ it towards that point on the perimeter. Terms that appear throughout the text are found in the center, whereas terms used in only part of the text are closer to that point on the oval. By putting both texts sequentially, we can see trends throughout both books. Terms on one side or the other are more common in their respective volumes. This spatial representation of textual frequency provides us with a unique perspective.

Ultimately, it is important to examine a book from a human standpoint combined with computer interpretation, as the computer has limitations in recognizing meanings of different words, but can process a large amount of text in a way that may avoid human error. While there is no replacement for human analysis, technology has given us the opportunity to analyze text in a word for word format that creates a more in depth interpretation of the poem.

Alex Lyman

Shelbi Davidson

Clarissa Thiriot

Dane Whitaker

Maddie Calder