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13 Blackbirds

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As someone who studies the “Digital Humanities,” I am fascinated by the ways computational systems contribute to our overall interpretive “ecologies.” At the same time, however, I find claims about distant reading, or “literary sociology,” to be overblown. This is not to say important insights haven’t been gleaned by taking such an approach, but by definition distant reading fails to engage with a single text, a single author, or an individual exegesis. But the same tools employed for distant reading can help us read more closely, and even more carefully, by outsourcing counting rather than reading.

With this in mind, I have created several simple Python functions—13 in all—for exploring some of things I discuss in the accompanying essay. These scripts are bundled into one file, called 14fn.py, which searches for prepositions, punctuation, words of affect, words of motion, etc. The vocabulary it employs is tied to the language used in Stevens’s poem.

The code for 14fn.py, as well as a copy of Stevens's poem, are available in this dropbox folder: 13blackbirds.

To analyze Stevens's poem with this script, you'll need Python 3 and a copy of Stevens’s poem as a .txt file. You'll also need to import the Natural Language Toolkit (nltk) and regular expressions (re). If you know how to run Python from terminal (or the command prompt), you’ll be all set. (If not, I recommend pythonanywhere, which is free and browser based.)

In addition to this script, a fourteenth function, presented via a simple but elegant flask interface created by Scott Svatos, is featured on this site's homepage.

———Lisa Swanstrom (2022)