Readings which are openly available are linked from this page. All other readings are on BruinLearn, under the module for the appropriate week.
CLASS 1 | JANUARY 11
In-class links
Projects to investigate
The Little Gidding Harmonies
Furnace and Fugue
Robots Reading Vogue
Digital Benin
I’m Still Surviving
Cruising Différance in 3 Scenes
Please sign up to help lead a discussion
You can now find the discussion schedule on the opening page of our BruinLearn site.
Full “How Did They Make That” lecture
CLASS 2 | JANUARY 18
What is digital humanities? (part 2)
Hockey, Susan. “The History of Humanities Computing.” In Companion to Digital Humanities.
Introduction to the Hockey reading
Terras, Melissa, and Julianne Nyhan. “Father Busa’s Female Punch Card Operatives.” In Debates in the Digital Humanities, edited by Matthew Gold and Lauren Klein, 2016 edition. Ann Arbor, Minn.: University of Minnesota Press, 2016. http://dhdebates.gc.cuny.edu/debates/text/57.
Data cleaning and manipulation
OPTIONAL
- Gregory, Ben. “Data Formats 101.” Astronomer, n.d. https://www.astronomer.io/blog/data-formats-101.
- Groskopf, Christopher. “The Quartz Guide to Bad Data.” Quartz.
To do for this class
In-class links
Download OpenRefine. Once you’ve done that, double-click on the application to be sure it opens. If you’re on a Mac and you get a warning that says “MacOS cannot verify the developer of OpenRefine.app,” please see these instructions.
Slides (Data basics)
OpenRefine tutorial (slides). If you’d prefer, you can download the same slides as a single PDF, or watch me complete the steps on video below.
CLASS 3 | JANUARY 25
Interrogating data
- Rawson, Katie, and Trevor Muñoz. “Against Cleaning,” July 6, 2016. http://www.curatingmenus.org/articles/against-cleaning/.
- Duarte, Marisa Elena, and Miranda Belarde-Lewis. “Imagining: Creating Spaces for Indigenous Ontologies.” Cataloging & Classification Quarterly 53, no. 5–6 (July 4, 2015): 677–702.
- Johnson, Jessica Marie. “Markup Bodies: Black [Life] Studies and Slavery [Death] Studies at the Digital Crossroads.” OR the video:
Data visualization
“Chapter Two: Choose an Effective Visual,” in Cole Nussbaumer Knafic, Storytelling with Data: Let’s Practice (Hoboken, NJ: Wiley, 2020), 51–105. (OK to skim!)
Niles, Robert. “Statistics Help for Journalists.” Robert Niles, n.d. https://www.robertniles.com/stats/. (You might look specifically at “Per capita and Rates” and “Standard Deviation and Normal Distribution.”)
Projects to examine
In-class links
Downloading Tableau Public
Tableau is available in various incarnations, including Public, Professional, and Education versions. It would make sense for us to use the version for education, but you need to request a key, which can take awhile. For now, we’ll use Tableau Public. The main difference between Public and Professional is that your data becomes public whenever you save your work.
Note: you may encounter problems if you have two different versions of Tableau installed on your computer; you’ll have to delete one.
Formatting spreadsheets
Dataviz principles and practices
Tutorials
Start here if you’re new to Tableau: Tableau 1: Getting Started with Tableau (just a PDF with linked video this time, no slides!)
Next (or first, if you’ve skipped the previous tutorial), you can move on to Tableau 2: Filters, Colors, and More (PDF with integrated video).
Or you can learn about Flourish, a web-based visualization tool (slides with integrated video; you can also download as a PDF).
If you’d prefer to code your own visualizations rather than use a tool, you can learn about P5.
CLASS 4 | FEBRUARY 1
Reconsidering data visualization
Johanna Drucker, “Humanities Approaches to Graphical Display,” Digital Humanities Quarterly 5, no. 1 (2011).
Introduction and chapter two: Klein, Lauren, and Catherine D’Ignazio. Data Feminism. Cambridge, Mass.: MIT Press, 2018, OR watch this video of their talk at Data & Society:
Text analysis
Kleymann, Rabea, Andreas Niekler, and Manuel Burghardt. “Conceptual Forays: A Corpus-Based Study of ‘Theory’ in Digital Humanities Journals.” Journal of Cultural Analytics 7, no. 4 (December 19, 2022). https://doi.org/10.22148/001c.55507.
Please watch the following text analysis lecture in advance of class. That way we’ll have more time for hands-on work. This version is annotated so that you can follow links; find a full-size version here.
Projects to examine
To submit for this class
In-class links
Download the Topic Modeling Tool (if you run into trouble, the TMT is also available on the lab computers)
Slides: Topic modeling with LDA
Self-paced tutorial: Messing Around with the Topic Modeling Tool (slides; also available as a PDF).
Self-paced tutorial: Visualize your topic model
CLASS 5 | FEBRUARY 8
Web design
- Tom Geller. Getting Started as a Full-Stack Developer. On LinkedIn Learning; you will need a Los Angeles Public Library card to access these videos. To log in to Lynda with your LAPL card, go here. (Let me know if you’re having trouble gaining access.) Please focus on Chapter 3, “Show Information with Display Technology.”
- de Ridder, Lennart. “10 Innovative Web Design Trends for 2019.” 99designs, December 12, 2018. https://99designs.com/blog/trends/web-design-trends-2019/.
Alternative for the tech-confident
On LinkedIn Learning, pick a front-end technology you’ve been wanting to learn and spend some time with the video and practice files. Suggestions: React.js, Node.js, JavaScript, Bootstrap, CSS frameworks.
Projects to examine
In-class links
Today, in the second portion of class, we’ll move through a series of five interlinked tutorials. You can also view the first and second tutorials as videos (haven’t gotten to the rest yet!).
HTML and CSS reference handouts
- Build a webpage from scratch with HTML and CSS
- Paint that page with CSS
- CSS Part 2: Divs, classes and IDs
- Publish your site with Github Pages
- Make a fancy site with Mural
If you already know HTML and CSS, my suggestion is to learn how to publish your site with GitHub (tutorial 3) or build a site with Mural (tutorial 4). You can also continue along the path you started this week by viewing LinkedIn Learning videos or use the time to make progress on your project.
To submit for this class
CLASS 6 | FEBRUARY 15
Rethinking design
Burdick, Anne. “Meta!Meta!Meta!: A Speculative Design Brief for the Digital Humanities.” Visible Language 49, no. 3 (December 1, 2015): 13.
Introduction from Miriam (Why did I assign this?)
Web mapping
- Sack, C. (2017). Web Mapping. The Geographic Information Science & Technology Body of Knowledge (4th Quarter 2017 Edition), John P. Wilson (ed.). DOI: 10.22224/gistbok/2017.4.11.
- McConchie, Alan, and Beth Schechter. “Anatomy of a Web Map.” http://maptime.io/anatomy-of-a-web-map/#0. (Please give this a moment to load and then click each slide to advance.)
Projects to examine
To submit for this class
CLASS 7 | FEBRUARY 22
Rethinking mapping
Introduction to this week’s reading
Turnbull, David. Maps Are Territories: Science Is an Atlas: A Portfolio of Exhibits. University of Chicago Press ed. Chicago: University of Chicago Press, 1993. Read Exhibits 1-6 and 10.
The Cartographer’s Dilemma (video)
Why All World Maps are Wrong (video)
“Critical Cartography” (The Occupied Times)
OPTIONAL:
Battersby, Sarah E., Michael P. Finn, E. Lynn Usery, and Kristina H. Yamamoto. “Implications of Web Mercator and Its Use in Online Mapping.” Cartographica: The International Journal for Geographic Information and Geovisualization 49, no. 2 (2014): 85–101.
“Critical cartography: subjectivity, politics, and power of spatial data,” Erica Nelson (video)
Projects to examine
To submit for this class
In-class links
Slides (basic network analysis concepts)
Create a simple network diagram with Flourish
Getting your data into the right format: edge list and node list
CLASS 8 | MARCH 1
Rethinking network analysis
Introduction to this week’s reading
Zer-Aviv, Mushon. “If Everything Is a Network, Nothing Is a Network.” Visualizing Information for Advocacy, January 8, 2016.
Kurgan, Laura, Dare Brawley, Brian House, Jia Zhang, and Wendy Hui Kyong Chun. “Homophily: The Urban History of an Algorithm.” E-Flux Architecture. https://www.e-flux.com/architecture/are-friends-electric/289193/homophily-the-urban-history-of-an-algorithm/. OR this video
Introduction to machine learning
Mimi Onuoha and Mother Cyborg, “A People’s Guide to AI” (Allied Media Projects)
Podcast: “Don’t Fall for the AI Hype” with Timnit Gebru, on Tech Won’t Save Us
Optional: This is the article Gebru refers to in the podcast: Bender, Emily M., Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell. “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? ?.” In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–23. FAccT ’21. New York, NY, USA: Association for Computing Machinery, 2021. https://doi.org/10.1145/3442188.3445922.
In-class links
Participatory slides (student-paced)
Big list of generative AI projects and tools
Gebru et al., “Datasheets for Datasets”
Stephen Wolfram, “What is ChatGPT Doing…and Why Does It Work?”
(A few) ethics + AI organizations & resources
- ACM Conference on Fairness, Accountability, and Transparency (FAccT)
- Past and upcoming workshops and events
- AI Now Institute at NYU
- Data & Society
- Oxford Internet Institute
- Algorithm Watch
- Center for Critical Internet Inquiry (C2I2) at UCLA
- Distributed AI Research Institute
- Algorithmic Justice League
CLASS 9 | MARCH 8
Project worktime (nothing due)
CLASS 10 | MARCH 15
Presentations