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 9/6 - Introductions

• Introductions
• Explore https://whatisdigitalhumanities.com/ (refresh the website several times)
  • In-class slides

Thu 9/8 - 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 1: 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
  • In-class slides

Week 2: Origins and Histories of “Digital Humanities”

Tue 9/13 - Origin Stories, Cultural Codes

• 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)
• Ruha Benjamin, “Introduction: The New Jim Code” from Race after Technology(2019) p. 1-32
  • In-class slides

Thu 9/15 - Anatomy of Code

• Read: Paul Ford, “What Is Code?” parts 1 & 2 (2015) {REMINDER: only read parts 1 and 2!}
• Due: Homework 2
• In-class practicum: Introduction to the command line

Week 3: Classification & Categorization

Tue 9/20 - 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
  • In-class slides

Thu 9/22 - What is Metadata?

• Read: Karl W. Broman and Kara H. Woo, “Data Organization in Spreadsheets,” (2018)
• Skim: the introduction to National Information Standards Organization’s primer “Understanding Metadata: What is Metadata, and What is it For?” (2004). – (Note: this is a long manual: Choose one standard to read about.
• Explore: datasets from The Pudding and datasets from our course’s curated list of datasets
• Due: Homework 3
• In-class practicum: Introduction to metadata + Python
  • In-class slides

Week 4: Locating Data

Tue 9/27 - 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
  • Mimi Onuoha’s “On Missing Data Sets” (2015)

Thu 9/29 - “Rehumanizing”” Data

‼️ NOTE: Dr. Eckert is traveling for conference - class meeting on ZOOM ‼️

• Read: Anelise Shrout, “(Re)Humanizing Data: Digitally Navigating the Bellevue Almshouse” (2018)
• Complete: Introduction to Python Basics tutorial [interactive cloud version]
• Due: Homework 4 [interactive cloud version]
• In-class practicum: Introduction to Python, continued [interactive cloud version]

Week 5: Making Data

Tue 10/4 - 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 10/6 - Making Data

• Read: Heather Krause, “Data Biographies: Getting to Know your Data” (2017)
• Read: MImi Onuoha, “The Point of Collection” (2016)
• Due: Data Biography
• In-class practicum: Working with data in Python, continued [interactive cloud version]

Week 6: The Materiality of the Digital

Tue 10/11 - 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)
• Read: Jill Lepore, “The Cobweb” (2015) Canvas PDF
  • Mini-exercise: explore the history of Google’s home-page with the WayBack Machine
  • In-class slides

Thu 10/13 - Web-Scraping

• Read: Brian Kernighan, “The World Wide Web,” from D is for Digital (2011) [Don’t be intimidated by the length of the PDF – a lot of the reading is an extended “glossary” of terms at the back]
• Read: Jeffrey Veen, “A Brief History of HTML” (1997)
• Due: [**DH Project Critique**](https://github.com/sceckert/IntroDHFall2022/blob/main/_assignments/dh-project-critique-assignment.md)
• Before practicum, read: Preparing for Web-scraping and OpenRefine
• In-class practicum: Webscraping and using OpenRefine
  • In-class slides

FALL RECESS

Tue 10/18 - No class

Thu 10/20 - No class

Week 7: Collecting Cultural Data

Tue 10/25 - 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
• Optional reading: Ed Folsom “Database as Genre: The Epic Transformation of Archives” (2007)
  • In-class slides

Thu 10/27 - 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 5
• ‼️Due: DH Project Critique ‼️ [RESCHEDULED DUEDATE]
• In-class practicum: Exploratory data analysis [interactive cloud version]] + Writing a project proposal

Week 8: Cultural Analytics

Tue 11/1 - 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
• Optional reading: Ted Underwood, “Appendices A & B: Data and Methods””
  • In-class slides

Thu 11/3 - Distant Reading

‼️ NOTE: Dr. Eckert is traveling for conference - class meeting on ZOOM ‼️

• Read: Richard Jean So, “All Models are Wrong” (2017) Canvas PDF
• Read: Nick Monfort, “Statistics, Descriptive and Inferential,” from Exploratory Programming for the Arts and Humanities (2021) [pages 225-239] 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 6
• In-class practicum: Text analysis and intro to git
  • In-class slides

Week 9: Text Analysis

Tue 11/8 Machine Learning, NLTK

Election Day - GO VOTE!

• 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)
  • In-class slides

Thu 11/10 - Topic Modeling

• Read: Ben Schmidt, “When You Have MALLET, everything looks like a nail” (2012)
• Due: Final Project Proposal
• Read through this short set of topic modeling set-up instructions
• In-class practicum: Topic modeling with MALLET. [interactive cloud version]

Week 10: Data Visualization & Network Analysis

Tue 11/15 - 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)
  • In-class slides

Thu 11/17 - 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: visualization: Working with Altair, mapping, networks, and topic modeling time series
  • In-class slides

THANKSGIVING BREAK

Tue 11/122 - No class (classes follow a Friday meeting plan)

Thu 11/24 - No class

Week 11: Access, Maintenance, Sustainability, and Preservation

Tue 11/29 - 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” <- In-class slides

Thu 12/1 - 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)
• In-class practicum: Keep working on projects! Review your proposal timeline
  • Guidelines for project presentations
  • Guidelines for final project
• In-class slides

Week 12: The Futures of Digital Humanities

Tues 12/6

• Read: Miriam Posner, “What’s Next: The Radical, Unrealized Potential of Digital Humanities” (2016)
  • Guidelines for project presentations
  • Guidelines for final project and final papers
• In-class slides

Thu 12/8

• Due: Presentation of final projects

Friday 12/16 - [Final Project Reflection Paper] (4-5 pages) DUE

• Guidelines for final papers