Course Schedule
Note: Your syllabus is a valuable reference document that you should regularly consult. It will be your map for the course. In it, you will find all policies, all major assignments, and a schedule of readings. Our readings are subject to change based on our interests as a class.
Week 1: Data in the Humanities
Tue 2/2 - Introductions
- Introductions
- Explore https://whatisdigitalhumanities.com/ (refresh the website several times)
- In-class slides
Thu 2/4 - What does humanities data look like
- Read: Daniel Rosenberg, “Data before the Fact” in “Raw Data” is an Oxymoron (2013) Canvas PDF
- Read: Edith Rickert, “To Skeptics” and “Introductory: Reasons and Methods,” in New Methods for Literary Study (1927)
- Due: Homework 0: Practice Rosenberg’s n-grams activity using Google Books Ngram Viewer and ECCO (log in using Princeton’s proxy access)
- In-class practicum: Counting by hand
Week 2: Origins and Histories of “Digital Humanities”
Tue 2/9 - Origin Stories
- Read: Tara McPherson, “Why Are the Digital Humanities So White? or Thinking the Histories of Race and Computation.” Debates in the Digital Humanities, ed. by Matthew K. Gold (2012)
Thu 2/11 - Anatomy of Code
- Read: Paul Ford, “What Is Code?” parts 1 & 2 (2015)
- Due: Homework 1
- In-class practicum: Introduction to the command line
Week 3: Classification & Categorization
Tue 2/16 - Classifications
- Read: Geoffrey Bowker and Susan Leigh Star, Chapter 1, Sorting Things Out: Classification and Its Consequences (1999) Canvas PDF
- Skim Chapter 2, Sorting Things Out Canvas PDF
- Read: Maris Elena Duarte and Miranda Belarde-Lewis, “Imagining: Creating Spaces for Indigenous Ontologies” (2015) Canvas PDF
Thu 2/18 - What is Metadata?
- Read: Karl W. Broman and Kara H. Woo, “Data Organization in Spreadsheets,” (2018)
- Read: the introduction to National Information Standards Organization’s primer “Understanding Metadata: What is Metadata, and What is it For?” (2004). Choose one standard to read about.
- Explore: datasets from The Pudding
- Due: Homework 2
- In-class practicum: Introduction to metadata + Python
Week 4: Locating Data
Tue 2/23 - Counting (who counts and for whom)
- Read: Catherine D’Ignazio and Lauren Klein, Data Feminism, Chapter 4: “What Gets Counted Counts” (2018)
- In-class slides
Thu 2/25 - “Rehumanizing”” Data
- Read: Anelise Shrout, “(Re)Humanizing Data: Digitally Navigating the Bellevue Almshouse” (2018)
- Complete: Introduction to Python Basics tutorial (interactive version here)
- Due: Homework 3
- In-class practicum: Introduction to Python, continued
Week 5: Making Data
Tue 3/2 - What is a DH Project?
- Watch: Miriam Posner, “How Did They Make That” (2014)
- Read: One review from Reviews in Digital Humanities.
- Project Critique: Choose one of the projects below as the object for your DH project critique
- Around DH in 80 Days (browse or find a project within)
- Shakespeare and Company Project
- Early Novels Database and dataset
- Frankenstein Variorum
- Torn Apart/Separados
- Black Quotidian
- Linked Jazz
- Missing Data (Mimi Onuoha) - project websites and project repository
- On the Books: Jim Crow and the Algorithms of Resistance
- Signs@40: Feminist Scholarship through Four Decades
- Quantifying Kissinger
- Mapping Indigenous L.A.
- Surfacing
- The Atlas of Surveillance
- HyperCities
- Documenting the Now
- Scribes of the Cairo Geniza
- Princeton Prosody Archive
- The Life and Death of Data
- The Colored Conventions Project
- Early Print
- Curricle Lens
- In-class slides
Thu 3/4 - Making Data
- Read: Heather Krause, “Data Biographies: Getting to Know your Data” (2017)
- Due: Data Biography
- In-class practicum: Working with data in Python, continued
Week 6: The Materiality of the Digital
Tue 3/8 - Encoding Cultural Data
- Read: Scott Weingart, “The Route of a Text Message” (2019)
- Read: Aditya Mukerjee, “I Can Text You A Pile of Poo, But I Can’t Write My Name” (2015)
Thu 3/11 - Web-Scraping
- Read: Jeffrey Veen, “A Brief History of HTML” (1997)
- Due: DH Project Critique
- Before practicum, read: Preparing for Web-scraping and OpenRefine
- In-class practicum: Webscraping and using OpenRefine
SPRING BREAK
Tue 3/16 - No class
Thu 3/18 - No class
Week 7: Collecting Cultural Data
Tue 3/23 - Archives, Datasets, and Public Humanities
- Read: Lauren Klein, “The Image of Absence: Archival Silence, Data Visualization, and James Hemings” (2013) Canvas PDF
- Read: Michelle Caswell, “Seeing Yourself in History: Community Archives and the Fight Against Symbolic Annihilation.” (2014) Canvas PDF
Thu 3/25 - Who is Data for?
- Read: Trevor Muñoz and Katie Rawson, “Against Cleaning” (2016)
- Roopika Risam, “Introduction: The Postcolonial Digital Cultural Record,” (2018) Canvas PDF
- Due: Homework for Week 7
- In-class practicum: Writing a project proposal + Exploratory data analysis
Week 8: Cultural Analytics
Tue 3/30 - Distant Reading
- Read; Ted Underwood, “Preface,” Distant Horizons: Digital Evidence and Literary Change (2018) Canvas PDF
- Read: Ted Underwood, “Chapter 2: The Life Spans of Genres,” Distant Horizons (2018) Canvas PDF
Thu 4/1 - Distant Reading
- Read: Richard Jean So, “All Models are Wrong” (2017) Canvas PDF
- Optional reading: Katherine’ Bode’s review of Distant Horizons, “Why you can’t model away bias” (2020), especially pages 113-120.
- Due: Homework for Week 8
- In-class practicum: Text analysis and intro to git
Week 9: Text Analysis
Tue 4/6 Machine Learning, NLTK
- Read: Ted Underwood, “Topic modeling made just simple enough” (2012)
- Read 3 very short pieces on data-driven methods method:
- Lincoln Mullen, “Isn’t It Obvious?” (2018)
- Matthew Lincoln, “Confabulation in the Humanities”(2015)
- Scott Weingart “Argument Clinic” (2017)
- Optional reading: Maciej Ceglowski “Deep-Fried Data” (2016)
Thu 4/8 - Topic Modeling
- Read: Ben Schmidt, “When You Have MALLET, everything looks like a nail” (2012)
- Due: Final Project Proposal
- In-class practicum: Topic modeling with MALLET
Week 10: Data Visualization & Network Analysis
Tue 4/13 - What is a humanities approach to graphs, maps, and charts?
- Read: Johanna Drucker, “Humanities Approaches to Graphical Display,” (2011).
- Skim through: Crystal Lee, Tanya Yang, Gabrielle Inchoco, Graham Jones, and Arvind Satyanarayan “Viral Visualizations:How Coronavirus Skeptics Use OrthodoxData Practices to Promote Unorthodox Science Online” (2021)
- Read: Georgia Luipi, “Data Humanism: The Revolutionary Future of Data Visualization” (2017)
Thu 4/15 - Networks
- Read: Scott Weingart, “Demystifying Networks” (2011)
- Explore: Giorgia Lupi and Stefanie Posavec, Dear Data
- Due: Close Reading of a Data Visualization
- In-class practicum: Maps and visualization: Working with matplot + Altair
Week 11: Access, Maintenance, Sustainability, and Preservation
Tue 4/20 - DH and global information infrastructures
- Read: Élika Ortega and Alex Gil, “Global Outlooks in Digital Humanities: Multilingual Practices and Minimal Computing,” (2016) Canvas PDF
- Read: Kate Crawford and Vladan Joler, “Anatomy of AI System”
- Link: Final Project Resources
Thu 4/22 - Sustainable DH? Glitches, Hacks, and Digital Ecologies
- Read: Wendy Hui Kyong Chun, “The Enduring Ephemeral, or the Future is a Memory,” (2008)
- Read: Kashmir Hill, “How an internet mapping glitch turned a random Kansas farm into a digital hell” (2016)
- Optional reading: Kris Paulsen, “The Index and the Interface” (2013)
- In-class practicum: Keep working on projects. Review your data preservation plan
- REVIEW: Final project resources document
Week 12: The Futures of Digital Humanities
Tue 4/27 - Final Projects
- Read: Miriam Posner, “What’s Next: The Radical, Unrealized Potential of Digital Humanities” (2016)
- Due: Presentation of final projects