Schedule

This list is subject to change according to the interests of the group and the direction our conversations take.

BEARINGS

Wk. 01 | Jan 31 | Introductions; Platforms; AI

Introduction to the Center for Digital Humanities, our allied centers on campus, the class, the platforms we’ll use, and how the latest conversations on artificial intelligence intersect with humanities research. Briefly: distributional semantics, generative text, research infrastructures across industry & academia.

🛝 slides

📖 readings

• Meredith Whittaker, “The Steep Cost of Capture,” Interactions 28, no. 6 (November 10, 2021): 50–55.
• Matthew Kirschenbaum, “Prepare for the Textpocalypse,” The Atlantic, March 8, 2023.
• James Somers, “A Coder Considers the Waning Days of the Craft”, The New Yorker, November 20, 2023.
• Adam Rogers, “Our Greatest AI Visionary Isn’t Sam Altman or Bill Gates. It’s Ted Underwood.,” Business Insider, December 2023.

THEORIES

Wk. 02 | Feb 07 | Histories of the Humanities

The history of science is a well-established field of research. What about the history of the humanities? This week we read accounts of the history of the humanities from antiquity to the present, and arguments for the distinct form of reasoning found in the humanities. Also: The idiographic and the nomothetic. The humanities’ relationship to truth claims. Pattern recognition across “the two cultures.” Then, data: tabular, tidy, structured, FAIR.

🛝 slides

📖 readings

• Eric Hayot, Humanist Reason: A History. An Argument. A Plan (Columbia University Press, 2021), Chapters 1 & 4.
• Helen Small, The Value of the Humanities, (Oxford: Oxford Univ. Press, 2013). Introduction.
• Rens Bod, A New History of the Humanities (Oxford: Oxford Univ. Press, 2014), Introduction: “The Quest for Principles and Patterns.”
• Recommended but not required
  • Jerry A. Jacobs, In Defense of Disciplines: Interdisciplinarity and Specialization in the Research University (Chicago ; London: University Of Chicago Press, 2014).
  • Barbara Herrnstein Smith, “What Was Close Reading? A Century of Method in Literary Studies,” Minnesota Review 87 (2016): 57–75.
  • Harvard libguide on close and distant reading: https://guides.library.harvard.edu/literature/closereading

🛠️ exercises

• Review list of departments and programs classified as Humanities and as Social Sciences at Princeton.
• Find an example dataset in your discipline (preferably a .CSV) that was the end product of some type of quantification, small or then big. Browse the following collections:
  • Matt Lavin’s Humanities Data
  • Melanie Walsh’s list of datasets
  • Miriam Posner’s list of datasets
  • Jeremy Singer-Vine’s Data Is Plural archive
  • The Pudding’s data repository
  • CDH-curated list of humanities datasets

Wk. 03 | Feb 14 | Histories of DH: From IBM Up to the Big Tent

How are DH scholars revising our understandings of the origins of DH as a discipline to include forgotten figures and the problematic origins of bureaucratic technologies? What did analog, manual approaches to quantification look like in the past? What was the state of “Big Tent” DH c. 2012? As we read about the use of older computing technologies, we’ll learn how to use the Unix command line and perform exploratory data analysis using a text-based program called VisiData.

🛝 slides

📖 readings

• Brad Pasanek, “Extreme Reading: Josephine Miles and the Scale of the Pre-Digital Digital Humanities,” ELH 86, no. 2 (2019): 355–85.
• Arun Jacob, “Punching Holes in the International Busa Machine Narrative,” in Alternative Historiographies of the Digital Humanities, ed. Dorothy Kim and Adeline Koh (Punctum Books, 2021), 121–44.
• Sharon M. Leon, “Complicating a ‘Great Man’ Narrative of Digital History,” in Bodies of Information: Intersectional Feminism and Digital Humanities, (Minneapolis: University Of Minnesota Press, 2018), 344-68.
• Alan Liu, “Where is Cultural Criticism in the Digital Humanities?” in Debates in Digital Humanities (2012)
• Jamie “Skye” Bianco, “This Digital Humanities Which is Not One,” Debates in the Digital Humanities 2012 (Minneapolis: University of Minnesota Press, 2012).
• Recommended but not required
  • Jerome McGann, “Philology in a New Key,” Critical Inquiry 39.2 (Winter 2013): 327-46.
  • Rachel Sagner Buurma and L. Heffernan, “Search And Replace: Josephine Miles And The Origins Of Distant Reading,” Modernism/Modernity cycle 3, issue 1 (April 11, 2018).
  • Alan Liu, “The Meaning of the Digital Humanities.” PMLA 128, no. 2 (March 2013): 409–23.
  • Yohei Igarashi, “Statistical Analysis at the Birth of Close Reading,” New Literary History 46, no. 3 (2015): 485–504.
  • Chris Alen Sula and Heather V. Hill, “The Early History of Digital Humanities: An Analysis of Computers and the Humanities (1966–2004) and Literary and Linguistic Computing (1986–2004),” Digital Scholarship in the Humanities 34, Supplement 1 (December 2019): 190–206.

🛠️ exercises

• Intro to the Command Line and VisiData, a command line tool for exploring tabular data. Load your sample CSV from last week into VisiData and describe its contents.
• Windows Subsystem for Linux (WSL) guide for Windows users
• Resources
  • Command Line Cheat Sheet
  • Visidata Cheat Sheet
  • Explain Shell: Full explanation of any command

Wk. 04 | Feb 21 | DH Today: Meaning & Signal

What is the state of the digital humanities today? How are institutions thinking about the intersection of data science with well-established DH methods? How do researchers from various disciplinary backgrounds construe “meaning” differently? Then: a workshop on data wrangling in OpenRefine with Bryan Winston, PUL Digital Scholarship.

🛝 slides

• Read one chapter relevant to your field from Debates in the Digital Humanities 2023, ed. Matt Gold & Lauren Klein, and come prepared to discuss.
• Barbara McGillivray et al., “The Challenges and Prospects of the Intersection of Humanities and Data Science: A White Paper from The Alan Turing Institute,” 2020.
• Anne Helmreich, Matthew Lincoln, and Charles van den Heuvel, “Data Ecosystems and Futures of Art History,” Histoire de l’art, no. 87 (June 29, 2021): 45–54.
• Lauren Klein, “Dimensions of Scale: Invisible Labor, Editorial Work, and the Future of Quantitative Literary Studies,” PMLA 135, no. 1 (January 1, 2020): 23–39.
• Recommended but not required
  • Rabea Kleymann et al., “Foreword to Special Issue on ‘Theorytellings: Epistemic Narratives in the Digital Humanities,’” Cultural Analytics 7, no. 4 (November 2022).
  • Antonija Primorac et al., “Distant Reading Two Decades On: Reflections on the Digital Turn in the Study of Literature,” Digital Studies / Le Champ Numérique 13, no. 1 (October 25, 2023).
• Exercise:
  • Introduction to OpenRefine, a tool for working with messy data. Bryan Winston, Digital Scholarship Specialist, Princeton University Libraries

Wk. 05 | Feb 28 | Is “DH” Now Just “H”?

Visit from Jeri Wieringa, Assistant Director, Center for Digital Humanities

🛝 slides

• Steven Ruggles, “The Revival of Quantification: Reflections on Old New Histories,” Social Science History 45, no. 1 (2021): 1–25.
• Underwood, McGrath, So, & Wellmon, “Culture, Theory, Data: An Introduction” to special issue, New Literary History 53, no. 4 (Winter 2023).
• Read one additional article relevant to your field from special issue on “Theory, Culture, Data”, New Literary History 53(4) and 54(1), and come prepared to discuss.
• Recommended but not required
  • Ted Underwood, “Theorizing Research Practices We Forgot to Theorize Twenty Years Ago,” Representations 127, no. 1 (August 1, 2014): 64–72, https://doi.org/10.1525/rep.2014.127.1.64.
  • Ian Milligan, “Illusionary Order: Online Databases, Optical Character Recognition, and Canadian History, 1997–2010,” The Canadian Historical Review 94, no. 4 (2013): 540–69.
• Exercise:
  • Intro to Jupyter notebooks. Right-click jupyter_intro.ipynb, then “save link as…”. Download the file to your computer, and open it using Visual Studio Code. Alternatively, navigate to Google Colab, sign into your institutional account, select File > Upload Notebook, and select the .ipynb file.
  • Browse Quinn Dombrowski’s list of “Jupyter notebooks for digital humanities.” Find a notebook relevant to your research or field, and try loading it in VS Code.

Wk. 06 | Mar 06 | Quantitative Methods: Models, Generalization, & Reproducibility

Visit from Jo Guldi, Full Professor of Quantitative Methods at Emory University

🛝 slides

• Jo Guldi, The Dangerous Art of Text Mining: A Methodology for Digital History, (Cambridge: Cambridge University Press, 2023). Excerpts.
  • Preface
  • Ch 4: Critical Search: A Theory
  • Ch 5: To Predict or to Describe?
  • Ch 14: The Future of the Art
• Also review Guldi & Buongiorno’s Hansard Viewer (covered in Chapter 8)
• Recommended but not required
  • Andrew Piper, Can We Be Wrong? The Problem of Textual Evidence in a Time of Data, Cambridge Elements in Digital Literary Studies (Cambridge University Press, 2020).
  • Theodore M. Porter, Trust in Numbers: The Pursuit of Objectivity in Science and Public Life (Princeton, N.J: Princeton University Press, 2020 [1995]). Excerpts.
  • Willard McCarty, “Modeling: A Study in Words and Meanings,” in A Companion to Digital Humanities (2004).
• Exercise: “Thinking About Semantic Change” (Jo’s handout on discourse surrounding environmentalism in Congress)
• Review and discuss final project options.

🏝️ Spring Break 🏝️

METHODS

Wk. 07 | Mar 20 | Scraping & Curating Structured Data

🛝 slides

• Katie Rawson and Trevor Muñoz, “Against Cleaning,” in Debates in the Digital Humanities 2019 (Minneapolis: University Of Minnesota Press, 2019).
• Henk Alkemade et al., “Datasheets for Digital Cultural Heritage Datasets” 9, no. 1 (October 30, 2023): 17, https://doi.org/10.5334/johd.124.
• Recommended but not required
  • Jessica Marie Johnson, “Markup Bodies: Black [Life] Studies and Slavery [Death] Studies at the Digital Crossroads,” Social Text 36, no. 4 (137) (December 1, 2018): 57–79, https://doi.org/10.1215/01642472-7145658.
  • Daniel Rosenberg, “Data Before the Fact,” in “Raw Data” Is an Oxymoron, ed. Lisa Gitelman (Cambridge: MIT Press, 2013), 15–40.
  • Marisa Elena Duarte and Miranda Belarde-Lewis, “Imagining: Creating Spaces for Indigenous Ontologies,” Cataloging & Classification Quarterly 53, no. 5–6 (July 4, 2015): 677–702, https://doi.org/10.1080/01639374.2015.1018396.
• Exercise:
  • “Python for Web Scraping,” with Filipa Calado, Digital Scholarship Specialist, Princeton University Libraries, using the Trans Legislation Tracker.
  • Install QGIS for next week.

Wk. 08 | Mar 27 | Maps & Spatial Humanities

• Trip to the PUL Map Library
• Workshop with Tsering Wangyal Shawa, GIS & Map Librarian, Princeton University Libraries. Introduction to digitizing historical maps, georectifying map images, and QGIS.
• Review of spatial humanities projects
  • In the Same Boats
  • Fabula and Sjužet in “Wandering Rocks”
  • Gent Gemapt
  • Computational Approaches to the History of Cartography
  • Mining and Mapping the Production of Space: A View of the World from Houston
  • Example of ArcGIS Storymaps made by PUL

Wk. 09 | Apr 03 | Artifacts & XR

• Trip to the PUL Makerspace
• Overview of infrastructure available to researchers for 3D modeling, scanning, and printing, and for cultural heritage augmented reality.
• Review of XR in humanities research
  • Sean Fraga, Booksnake (USC)
  • Massimo Riva, Shadow Plays (Stanford UP)
  • Digital Giza (Harvard 2013), with a paper about its creation and use
  • TU-CULT (Venice 2017), and associated paper

Wk. 10 | Apr 10 | Very Distant & Very Close

Visit from Laure Thompson, Research Software Engineer, Center for Digital Humanities, to discuss topic modeling.

Trip to PUL Digital Imaging Studio to see Selene photometric stereo scanning system.

• Richard Jean So, “‘All Models Are Wrong,’” PMLA 132, no. 3 (May 2017): 668–73, https://doi.org/10.1632/pmla.2017.132.3.668.
• Lisa Rhody, “Topic Modeling and Figurative Language” (2012) for an overview of topic modeling
• Recommended but not required
  • Maria Antoniak, “A Computational Reading of a Birth Stories Community” (2019)
  • Dong Nguyen et al., “How We Do Things With Words: Analyzing Text as Social and Cultural Data,” Frontiers in Artificial Intelligence 3 (August 25, 2020): 62, https://doi.org/10.3389/frai.2020.00062.

Wk. 11 | Apr 17 | Refusal

• Lauren Klein, “Are Large Language Models Our Limit Case?” Startwords, no. 3 (August 2022).
• Matthew N. Hannah, “Toward a Political Economy of Digital Humanities”, in Debates in the Digital Humanities 2023
• Cifor et al., “Feminist Data Manifest-no” (2019)
• Recommended but not required
  • Nan. Z. Da, “The Computational Case against Computational Literary Studies” (2019), and short responses to Da’s piece in “Computational Literary Studies: A Critical Inquiry Online Forum” (April 1-3, 2019)
  • Miriam Posner, “What’s Next: The Radical, Unrealized Potential of Digital Humanities” (2016)
  • Inioluwa Deborah Raji et al., “AI and the Everything in the Whole Wide World Benchmark,” 2021, https://doi.org/10.48550/arXiv.2111.15366.

PROJECTS

Wk. 12 | Apr 24 | Project Proposal Presentations

• Prepare and discuss, in this closing week, your final projects.
• Potential discussion of computational portion of dissertation in preparation for Graduate Certificate in DH.