Schedule

Readings which are openly available are linked from this page. All other readings are on CCLE, under the appropriate week. Further reading isn’t exhaustive; it’s usually stuff I wanted to put on the syllabus but couldn’t find room for.

CLASS 1 | OCTOBER 2

Slides. See also this video for a walkthrough of reverse-engineering a DH project.

Introductions

What is digital humanities?

CLASS 2 | OCTOBER 9

What is digital humanities? (part 2)

• Hockey, Susan. “The History of Humanities Computing.” In Companion to Digital Humanities, edited by Ray Siemens, John Unsworth, and Susan Schreibman. Blackwell Companions to Literature and Culture. Oxford: Blackwell Publishing Professional, 2004. http://www.digitalhumanities.org/companion/.
• 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 & manipulation (part 1)

Slides

• 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.

Projects to examine

• The Valley of the Shadow
• The Rossetti Archive
• The Perseus Digital Library

Homework and further reading

CLASS 3 | OCTOBER 16

Data cleaning & manipulation (part 2)

• Rawson, Katie, and Trevor Muñoz. “Against Cleaning,” July 6, 2016. http://www.curatingmenus.org/articles/against-cleaning/.
• Johnson, Jessica Marie. “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.
• 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.

Data visualization (part 1)

Slides

• Cairo, Alberto. The Functional Art: An Introduction to Information Graphics and Visualization. Berkeley, CA: New Riders, 2013. Chapters six and eight.
• 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

• NovelTM: Text-Mining the Novel
• Colored Conventions
• Missing Datasets

Homework and further reading

CLASS 4 | OCTOBER 23

Data visualization (part 2)

• 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.

Text analysis (part 1)

Slides.

• Ted Underwood. “Seven Ways Humanists Are Using Computers to Understand Text.” The Stone and the Shell (blog), June 4, 2015. https://tedunderwood.com/2015/06/04/seven-ways-humanists-are-using-computers-to-understand-text/.
• Clement, Tanya E. “‘A Thing Not Beginning and Not Ending’: Using Digital Tools to Distant-Read Gertrude Stein’s The Making of Americans.” Literary and Linguistic Computing 23, no. 3 (September 1, 2008): 361–81.

Projects to examine

• The Shape of History
• The Knotted Line
• Signs at 40

Homework and further reading

CLASS 5 | OCTOBER 30

Text analysis (part 2)

• Binder, Jeffrey M. “Alien Reading: Text Mining, Language Standardization, and the Humanities.” 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/69.
• Schmidt, Benjamin M. “Words Alone: Dismantling Topic Models in the Humanities.” Journal of Digital Humanities, April 5, 2013. http://journalofdigitalhumanities.org/2-1/words-alone-by-benjamin-m-schmidt/.
• McPherson, Tara. “Why Are the Digital Humanities So White?” In Debates in the Digital Humanities, edited by Matthew K Gold, 139–60. Minneapolis: University Of Minnesota Press, 2012. http://dhdebates.gc.cuny.edu/debates/part/4

Web design (part 1)

Slides

• Williamson, James. Web Development Basics: Web Fundamentals. On Lynda.com; you will need a Los Angeles Public Library card to access these videos. To log in to Lynda with your LAPL card, go here.
• de Ridder, Lennart. “10 Innovative Web Design Trends for 2019.” 99designs, December 12, 2018. https://99designs.com/blog/trends/web-design-trends-2019/.

Projects to examine

• Journal of Cultural Analytics (just skim, obviously)
• Vectors Journal of Culture and Technology in a Dynamic Vernacular (ditto)
• Creating Data: A Guided Tour of the Digital Library

Homework and further reading

CLASS 6 | NOVEMBER 6

Slides

Web design (part 2)

• Burdick, Anne. “Meta!Meta!Meta!: A Speculative Design Brief for the Digital Humanities.” Visible Language 49, no. 3 (December 1, 2015): 13.

Web mapping (part 1)

Slides (mapping terms to know)

• 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

• Digital Harlem
• Digital Gazetteer of the Song Dynasty
• Mapping Indigenous L.A.

Homework and further reading

CLASS 7 | NOVEMBER 13

Web mapping (part 2)

• 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.
• 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.

Network analysis (part 1)

Slides (basic network analysis concepts)

• Scott Weingart, “Demystifying Networks, Parts I & II,” Journal of Digital Humanities 1:1 (Winter 2011).

Projects to examine

• Star Wars Social Networks 
• They Rule

Homework and further reading

CLASS 8 | NOVEMBER 20

Network analysis (part 2)

• Zer-Aviv, Mushon. “If Everything Is a Network, Nothing Is a Network.” Visualizing Information for Advocacy, January 8, 2016. http://visualisingadvocacy.org/blog/if-everything-network-nothing-network.
• 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/.

Intro to machine learning

Slides

• Julia Angwin et al., “Machine Bias,” ProPublica, May 23, 2016.

Homework and further reading

CLASS 9 | NOVEMBER 27

NO CLASS

CLASS 10 | DECEMBER 4

Presentations