It’s the end of the semester, and as usual things are crazy. I’ve finally got my Peanuts experiment up and running, which means people are coming in to participate. A lot of people. The experiment lasts an hour, and between last week and this week, I’ll run 24 subjects, which means I’ll have lots of data to pour over during winter break.
In the meantime, I also finished coding several strips from Peanuts, and have found several interesting things. For this experiment, I culled 180 strips from the first two Complete Peanuts volumes (kindly donated by Fantagraphics), which were either silent or I altered to become silent. I then coded them all panel-by-panel. That’s 720 panels, and yes, it took me all semester.
So, what did I find in my sample? Well, there is some interesting stuff…
Most of what I coded for has to do with narrative structure, or what I would call visual grammar. I’m hoping my redone terminology is transparent enough to follow here.
Out of 180 strips, 140 of them (78%) used “Establishers” to set up information in the first panel. Conversely, 123 of them (68%) finished with a “Release” where the tension of the narrative dissipates. 135 (75%) also use an “Initial” as the second panel, which initiates the actions of the strip. 112 (60%) finish the strip with a “Peak” — the height of narrative tension.
Of 180 strips, 50% (90) use the overall structure of “Establisher-Initial-Peak-Release.” The next highest isn’t even close, with only 13 strips using the pattern “Establisher-Initial-Initial-Peak.”
The “E-I-P-R” pattern is what I think of as the canonical narrative arc (which on a macro scale resembles the traditional “narrative arc” of plotlines). All this aligns even more interestingly to coding I did of event structures for each characters’ actions, but describing all that here might be a little overkill.
Just as a reminder, this is a very specific sample of strips and shouldn’t be construed as making any sort of claims overall about Peanuts. Nonetheless, its fun to see what info the strips alone hold. Now I’m even more excited to see what the results of my study show about people’s behavior in relation to these coded predictions.