June 03, 2025

Words as Data and Intro to Python

Before the session

Install Python and JupyterLab

  1. Setting up Python and Jupyter Lab: We will work in Python and Jupyter Lab during the fellowship. To set up, follow steps 1-3 in “Install Python & Jupyter Lab” section of Introduction to Cultural Analytics and Python, v.1 (Walsh, 2021). You can stop following the tutorial after step 3; you don’t have to download VS Code for the Summer DH program! If you’re new to using Jupyter Lab or a coding enviornment, you can also read How to Use Jupyter Notebooks.
  2. Learning the command line: Review “the Command Line” lesson from Introduction to Cultural Analytics and Python, v.1. Start from the beginning of the lesson and feel free to pause when you get to the “Working with Files and Texts” section.

Readings

I will list the readings in order of importance. If you’re limited on time, prioritize the ones listed at the top.

  1. Nguyen, Dong, et al. “How We Do Things With Words: Analyzing Text as Social and Cultural Data.” Frontiers in Artificial Intelligence, vol. 3, Aug. 2020, p. 62. DOI.org (Crossref), https://doi.org/10.3389/frai.2020.00062.
  2. Cottom, Tressie McMillan. “‘47. More Scale, More Questions: Observations from Sociology’ in ‘Debates in the Digital Humanities 2016’ on Debates in the DH Manifold.” Debates in the Digital Humanities. 2016.

During the session

Hour one: Check-in notes and Readings discussion

  1. Cottom (2016) notes that “We do distant reading because we can. But that we can do it—these data, these methods—is inherently political.” Unpack that with me: What points from her piece (or from other readings) underscore this point for you? How does that idea resonate (or not) with the data you’re choosing to work with this summer?
  2. Let’s explore some of the questions at the end of Nguyen et al.’s (2020) piece. Do any stick out to you?

Hour two: Check-in and Introducing Python (50 mins)

  1. Check-in (15 minutes): Go around the room, share how far you’ve each gotten with the pre-work. What’s been your experience so far? What questions are coming up?
  2. Introducing Python (25 mins) We’ll talk about the bigger picture of how we can use Python in our text analysis workflows. We’ll base our discussion on “Anatomy of a Python Script” from Walsh (2021).
  3. Any remaining time: Help troubleshooting any installation issues.

After the session

  1. Reflection post: where meaning lies in your texts.
  2. Session pre-work for tomorrow.