This past week for my History and New Media class I had to read selections from Geoffery Rockwell and Stefan Sinclair’s book Hermenueutica, which illustrated how different digital humanities projects can use visualizations. Along with the reading, we were tasked with trying out Voyant Tools.
During the reading, and the in-class demonstration, I became particularly fascinated by Voyant’s “ScatterPlot” function, which visually represents a “correspondence analysis” (how closely related terms and data sets are to one another) on a 2D plane via physical proximity. i.e. The closer two words, two data sets, or a word and a data set are to each other on the plot, the closer the analytic relationship.
During the in-class demonstration, I was also intrigued by the ability to edit the “stop-word” list (the list of terms that are excluded from analysis). Voyant automatically uses a default list that includes very commonly used terms such as articles, prepositions, and pronouns (the, an, in, this, they, etc.). I found, however, that some of those words were actually of interest to me in trying to understand how an individual might be using terminology. Specifically, I was interested in seeing the uses of pronouns. How much were individuals using “we” vs “I” vs “you” vs “they”. These words very much have implications as to the kind of rhetoric an individual is engaging in. A term like “we” is inherently inclusive. But if someone is using “them” and “us” to a greater degree, are they engaging in otherwise divisive rhetoric or is there possibly some other explanation?
To analyze such rhetoric I took the textual corpus of Milwaukee Mayor (1960-1988) Henry Maier (which included documents from both myself and another student) and uploaded it to Voyant. I then changed the stop-word list from the default setting to having no stop-words. I could then see, using the word cloud tool, which of all the words were most prevalent. Using the word cloud as a guide, I could then create a customized stop-word list, taking out articles and prepositions but leaving in the pronouns I wanted to analyze.
Using this method I did find some interesting correlations using the ScatterPlot. Maier’s mentions of “we” correspond strongly with the terms “city” and “Milwaukee”. Not surprisingly, given his position, he uses the inclusive pronoun when he’s invoking a sense of city-wide community. Interestingly, the pronouns “I”, “you”, and “our” cluster around each other. I might have expected “our” to be more strongly associated with the “we/city” correlation. The “I/you/our” cluster is also much more strongly associated with Maier’s use of racial terminology such as “negro” and “white”. “They” and “their” seem to be outliers, they cluster together, but the only other term nearby is “because”. Perhaps Maier is using these 3rd person plurals in some type of explanatory manner? To check this hypothesis I used the “WordTree” tool. As soon as I opened the tool, WordTree showed the word “because” as the most common word immediately preceding “they”. Following the phrases forward and backward, one seemed to be an explanation as to protestors getting purposefully arrested, the other an explanation of housing problems caused by white flight (Maier uses the class term “rich” in place of the racial term “white”).
WordTree for Maier corpus – Voyant Tools
There’s so many tools, and so many varied ways you can use them, that I’ve only barely scratched the surface. I’m excited to dive deeper and start comparing other figures of the Milwaukee Civil Rights movement. Stay tuned for more as the semester’s project progresses.