Unfortunately, I lost my first Wordle of War of the Worlds, which had a beautiful custom palette and Martian-like font, and now I’m really mad that I couldn’t find a search function on the Wordle site’s public gallery. Boo. So here’s a second one.
And, the much uglier WordItOut!
Interestingly, many configurations of the Wordle sketch out a bare-bones premise for the book with the most prominent words: “Martians Came”. Both “Mars” and “Earth” are very small, and don’t even appear in the WordItOut! There are few proper nouns, no character names, but places like “London” and “Woking” show up. “Black” and “red” are also prominent, as are sensory words like “heard”, “see”, “saw.” “Seemed” is much bigger than “know,” giving a feel for the uncertainty that haunts much of the action of the book. The WordItOut! on the other hand, picked up much more common “filler” words like “said,” “about,” “through,” “over.” It was also much less fun to play with. Much of the appeal of the Wordle for me was arranging the layout so as to maximize the “sense” I could make out of it visually: how much of the basic “plot” or action words could I manage to juxtapose and highlight with color, straight or curved lines, font “appropriate” to the subject matter? As Ramsay suggests, this is perhaps the greatest potential of text-analysis tools–the ability to operate at a new scale and to manipulate the text on different levels than “close reading” allows.
Not surprisingly, very few of my Wordle words were allowed in the Up-Goer Five Text Editor. While experimenting with Up-Goer Five, I was trying to figure out the best approach–do I hand-pick words from the list of ten hundred, or do I build my definition by attempting to write it first, and then “translate” it? I wove back and forth between these approaches, picking some words and then trying out other phrases that were inspired by them. Ultimately I was disappointed, and I must say my definition of DH was more flippant than informative: “Many conversations about building, making, thinking. doing; money, jobs. Using computers to study humans and read/write ‘algorithmically.’” Without punctuation it’s as long as a tweet.
When I input the Wordle text into the CLAWS Part-of-Speech tagger, it interestingly read many of the verbs as gerunds, tagging them as adjectives. I would really like to know what others think the best application of a tool like this would be. I immediately thought it could be used as a translation aid from one corpus to another, but this doesn’t seem to be a feature.
TAPoR was honestly the tool that got me most excited and seemed most applicable to my research on women’s alternative/independent publishing. It was easy to “mess around” in–I’ve never done any text analysis before but at the most basic level I knew what a stop-word list was, and could figure out how to get the tool to “spit out” what I wanted to see. The descriptions that appear when you hover over a tool were immensely helpful and I found myself wishing every DH project or toolbox had this feature. Interested by the appearance of place names like London and Woking, I graphed these on the concordance tool to see the protagonist’s (and the Martians) geographical movements through the novel. I also graphed “Martians” and “People,” the occurrence of which mirrored each other for most of the novel before “People” drops off sharply toward the end, when the protagonist is moving through deserted houses and communities. This exercise really tested my knowledge of the “plot points” in the book–I found myself remembering details that seemed insignificant, all by looking at a graph of the words. I’m just itching to digitize some zines, scrape their text, and compare all the instances of “queer,” “feminist,” and “anti-racist” I can find.
I also couldn’t help but smile at the title of these tools: “Voyant: See through Your Texts.” The entendre is irresistible–use “your texts” (whatever they may be) as a pane or a lens through which to view a specific topic, and/or make your texts transparent, lucid; make bare their meanings. Of course, the implication of Ramsay’s argument is that none of these tools, or the texts to which we apply them, are “transparent.” We might be able to “see” our text differently, from new angles an at previously hidden layers, but it is dangerous to assume that nothing resists the self-evidence of scholarly vision. My partner, who was watching me do these experiments and also helping me with the necessary plugins to run them, kept lingering on these sites to figure out what kinds of algorithms they use and what kinds of patterns they’re finding. I’m not sure most users think about the tools on those levels [DH-ers and hackers are, as usual, another story], and it would be easy to tout their potential while forgetting that our interpretations, the most valued currency in some humanities disciplines, are just begging to be made.