Module 8: Textual Analysis and Data Mining
3 March 2022
Welcome back from Reading Week!
So much of our cultural record has been digitized. How can we use computers to “read” texts for us? Should we?
Readings for this Week
- Jo Guldi and David Armitage, The History Manifesto (Cambridge: Cambridge University Press, 2017), ch. 4. Can access open access PDF or HTML.
- Jo Guldi, “Critical Search: A Procedure for Guided Reading in Large-Scale Textual Corpora,” Journal of Cultural Analytics, 19 December 2018. https://culturalanalytics.org/article/11028-critical-search-a-procedure-for-guided-reading-in-large-scale-textual-corpora
- Jean-Baptiste Michel et al., “Quantitative Analysis of Culture Using Millions of Digitized Books,” Science 331,no. 6014 (January 14, 2011): 176–82. Available via library database.
- The Programming Historian. https://programminghistorian.org (see homework)
Homework for the Week
In addition to the readings, I would like you to visit the Programming Historian and explore some of the lessons in the English-language version. Pick one. I don’t expect you to try it out, but I’d like you to familiarze yourself with it and ask yourself the following questions:
- What problem is this lesson trying to solve?
- Does it look like something I could learn?
- How could I imagine using this in my own work?
Our Discussion for the Week
This week, we’ll be focusing on a few different topics:
- What is “big data” and why should historians care?
- What kinds of approaches have historians fruitfully used when it comes to computational analysis? What do we gain from this kind of work? Do we lose anything?
- Should historians become programmers? If yes, how? If no, why not?
Want to Meet with Me?
As always, you can book a 30-minute meeting with me via Calendly. Use this link here. If there are no times that are available, just send me an email and we can work something out.
This will create a Microsoft Teams appointment. The URL for the Teams link will be in the calendar invitation e-mailed to you.