Re-learning the ropes of Voyant
So, the tool for this week’s HIST 8500 seminar wasn’t totally new to me–I took an online class through EdX some years ago that spent some time on Voyant Tools. I’ll say that I could approach it with a lot more theoretical understanding this time around, though! I was going to go through a poem I translated for a conference paper once and run that through Voyant, but it turned out that it took way too much time to strip out my own amateurish translation and just leave the Latin text, so I just went with the documents provided for the assignment and went to town!
The word cloud, or “Cirrus,” was probably the most familiar tool to me, both because of my prior experience with Voyant and because word clouds get used all the time! One thing I did more with this time, though was experiment with scale and the number of terms included in the cirrus. I liked that you can choose to scale it by the entire corpus or just by an individual work–here’s what it looked like when I limited the scale to just “10_1915”:
This seems like a really useful way to track changes over the different works of a corpus.
I learned two things from trying to export the reader tool:
- Cleaning up your OCR really is important! When it tells me that “Ameriean” appears only once in the document, I totally believe it! It was interesting to me when scrolling down that the errors seemed less frequent–I wonder if that’s because the title was originally in a fancier font or something.
- You actually do need a plugin if you want to export the tool as a live, active tool rather than a screencap–Wordpress really doesn’t handle iframe embeds well at all without a plugin. I went with “Advanced iframe”–we’ll see how well that serves me!
There really are a ton of tools to pick from–my first time playing around with Voyant, I think I pretty much only stuck to the default ones: Cirrus, Reader, Trends, Summary, and Contexts. But the “Click to choose another tool” button revealed a lot I didn’t even know about!
Having played around with it a bit, I think some of my favorites (besides the default tools) were MicroSearch (offers a really cool visualization of where a word appears in a text and also in the corpus as a whole, which would be really useful for me in tracking the role of a character over a longer text or body of texts), Collocate (shows very clearly how often certain words are paired together or placed near each other), and TermsBerry (another one that easily illustrates how often commonly-used words are paired together. Some of the other tools looked cool, but I haven’t quite figured out what I might use them for. I guess that speaks to the need to think carefully about what information you’re trying to convey with quantitative visualizations, and what visual language might be best for that purpose. In any event, it’s exciting to know how many possibilities there are for quantitative textual analysis, and I think I’m better equipped than I was a few years ago to figure out how this might all be useful for me!