Mark Z. Danielewski’s short story, “Clip4,” begins as if it were an academic paper and later becomes a narrative in which Toland Ouse acts rather than analyzing the film clip. Because of this transition, there should be more concrete words about time and space during the narrative as Toland moves around. Using the tool Voyant, I data mined Clip4 to discover if this were true. I could not find a tool that would pick out words by category, and so I searched through the terms list to find them. To record the words, and their frequency, I used excel, which was probably overkill. Choosing which words to use also proved difficult. For instance, for words relating to time, should I use “moments?” I chose not to because it was not concrete enough, but in hindsight, I wish I would have. Should I use the words “wall” and “windows,” even though one could not generally occupy them? I chose to because they bound the places that we can occupy.
The activity would not have been possible without the visualization tools since I was looking for change over the course of the text. Clicking on a term brought it up in the Trends graph, and I entered the terms into the Bubblelines visualization. As you can see, the instances where time-related words appeared is somewhat more spread out than place words. However, both time and place-related terms increase with narration. It is also possible to track the movement of time. For instance, “afternoon” appears more frequently just before “night.” And most of the action happens at night because it appears more. While Clip4 is a short story and has obvious movement from abstract thinking to in the world acting, using a similar process with more detail and more words – for instance, objects in space – could prove useful for larger works and comparisons between works.
| Time Words | Frequency | Place Words | Frequency |
|---|---|---|---|
| day(s) | 8 | wall | 9 |
| night | 10 | water(s) | 9 |
| afternoon | 2 | home | 5 |
| evening | 3 | kitchen | 4 |
| year(s) | 8 | place | 4 |
| months | 1 | windows | 3 |
| minutes | 1 | world | 3 |
| surface | 2 | ||
| university | 2 | ||
| bedroom | 1 |
Unfortunately, the visualizations did not come with a word legend. Which is weird.
Time Words
Place Words
Gelphi was interesting to work with, but a bit confusing to me. Still, once I started working with it, I saw how it could add insight. It is difficult for an AI to connect words together based on their relationship to each other. But humans who are reading the story can make those connections. So having an ability to create my own node words and edge connections allowed me to think more deeply about where things were in relation to each other. In this story, and because of the number of words I chose, words about place seemed like they would yield the most results. In this part, I ended up going back to the story myself and ‘data mining” each word to see its context. I realize, in writing this out, I could have done that in Voyant! Still, sometimes putting my own eyes on the text is good.
I am wondering how useful gelphi could be in mapping historical evidences to make an argument? I’m thinking, for instance, if two events that seem to be separate turn out to be related due to the people involved, or a previous event. I think you get the picture.
I connected water to so many things because it was seen on the wall, which was in the kitchen, and it invaded the home when Audra drowned. The small triangle is where the invisible camera filmed Clip 4. I almost didn’t attach the bedroom to anything, but realized it had some connection to academy stuff and Toland’s awareness, and so kind of connected it to the university. The university’s connection to the home is because Toland, from the university, came to the home and because the word also refers to Toland going home. Also, the academy studied the home.
I found myself struggling with this assignment, but it turns out this was a good thing. Sometimes, to gain understanding one must practice, and in my practice here, I learned new ways of making connections. Also, Voyant could be used for diary entries or transcripts of speeches, interviews, etc which would be good not just for literary analysis, but also for historical analysis. Barbara Welter, in her 1966 article “The Cult of True Womanhood: 1820-1860” (a foundational piece in women’s history) was doing some textual analysis on articles written by and/or for women about their lives. Technology like this would have helped her a lot.
