Schedule for English 197 (S 2024)
Introduction to Digital Humanities
Introduction
Close vs. Distant Reading
Class 2 (April 4, 2024)
Readings
- Cleanth Brooks, “The Heresy of Paraphrase” (1947)
- Jean-Baptiste Michel, Erez Lieberman Aiden, et al., “Quantitative Analysis of Culture Using Millions of Digitized Books” (2011) [paywalled; UCSB students have free access through the campus network or from off-campus through the UCSB VPN or Library Proxy server]
Class 3 (April 9, 2024)
Readings
- Franco Moretti, Graphs, Maps, Trees (2007), pp. 1-33
[Purchase this book, available at the UCEN bookstore]
Text Encoding
Class 4 (April 11, 2024)
Readings
- William Warner, Kimberly Knight, and UCSB Transliteracies History of Reading Group, “In the Beginning was the Word: A Visualization of the Page as Interface” (Note: the original Flash animation, which was interactive, is no longer viewable because the Flash program reached “end of life” at the end of 2020 and is no longer supported in current browsers and operating systems. View instead the MP4 video version, or download the AVI or WMV video versions.)
- Yin Liu, “Ways of Reading, Models for Text, and the Usefulness of Dead People” [PDF or HTML] (2013)
Class 5 (April 16, 2024)
Readings
- Alan Liu, “Transcendental Data: Toward a Cultural History and Aesthetics of the New Encoded Discourse” (2004) (read only pp. 49-57)
Text Analysis
Class 6 (April 18, 2024)
Readings
- Ryan Heuser and Long Le-Khac, “A Quantitative Literary History of 2,958 Nineteenth-Century British Novels: The Semantic Cohort Method” (2012)
Class 7 (April 23, 2024)
Text Analysis (Topic Models)
Class 8 (April 25, 2024)
Readings
- David M. Blei, “Probabilistic Topic Models” (2013) — (read only to end of p. 79, before the math begins)
- Ted Underwood, “Topic Modeling Made Just Simple Enough” (2012)
Class 9 (April 30, 2024)
Readings
- Andrew Goldstone and Ted Underwood, “The Quiet Transformations of Literary Studies: What Thirteen Thousand Scholars Could Tell Us” (2014)
- Andrew Goldstone, Topic model of 100 years of literary criticism journals (visualized in Goldstone’s Dfr-browser interface)
Class 10 (May 2, 2024)
Readings
- Andrew Goldstone et al., Topic model of 40 years of the Signs journal of “Women in Culture and Society” (visualized in Goldstone’s Dfr-browser interface)
- Helpful in learning how to work with Dfr-browser is the guide page on “Interpreting the topic model of Signs“
- Andrew Piper, excerpt from “Topoi (Dispersion),” in Enumerations: Data and Literary Study (2019) — read only pp. 66–75 [available on course Canvas site]
Class 11 (May 7, 2024)
Readings
- Background Readings in Linguistics Theory
- Ferdinand de Saussure, Course in General Linguistics (1916) – read pp. 114-117, 123-27.
- J. [John] R. [Rupert] Firth, “A Synopsis of Linguistic Theory, 1930-55” (Oxford: Blackwell, 1957) – read sections III-IV (pp. 7-13) [available on course Canvas site]
Text Analysis (Word Vectors / Word Embedding)
Class 12 (May 9, 2024)
Readings
- Luis Serrano, “What Are Word and Sentence Embeddings?” (2023)
- Optional: create an account on the Cohere site mentioned in the article and try the “embedding” function in the Cohere “playground.” (See an example of results.)
- Saptarashmi Bandyopadhyay et al., “Word Embedding Demo: Tutorial” (2022) — Note: The actual interactive demo accompanying this tutorial about word embeddings (or word vectors) is assigned for the second part of Practicum 5.
- Nika Mavrody, Laura B. McGrath, Nichole Nomura, and Alexander Sherman, “Voice” (2021) — Read the “Abstract” and pp. 155-164.
Class 13 (May 14, 2024)
Readings
- Ryan Heuser, “Word Vectors in the Eighteenth Century” (conference proceedings abstract) (2017)
- Optional: If you are interested, you may wish to read Ryan Heuser’s series of blog posts about word embedding linked from this page on his blog (with individual posts on “Concepts,” “Methods,” “From Fields to Vectors,” and “Semantic Networks”).
AI (Large Language Models)
Class 14 (May 16, 2024)
Readings
- Chris Woodford, “How Neural Networks Work: A Simple Introduction” (2023)
- Cornellius Yudha Wijaya, “Large Language Models Explained in 3 Levels of Difficulty” (2024)
- Optional: For a slightly deeper, more detailed explanation of neural networks as part of an explanation of large language models, see Andreas Stöffelbauer, “How Large Language Models Work: From Zero to ChatGPT” (2023).
- Minh Hua and Rita Raley, “Playing With Unicorns: AI Dungeon and Citizen NLP” (2020) [If you can’t finish this article by this class, try to read at least the first two sections; and then finish the rest of the article for the next class.]
Class 15 (May 21, 2024)
Readings
- Emily M. Bender et al., “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” (2021)
- [Optional: If you are interested in the controversy and background behind this article, see Tim Simonite, “What Really Happened When Google Ousted Timnit Gebru” (2021)]
- Alan Liu, “What Is Good Writing in the Age of ChatGPT?” (Commencement Address for the UCSB English Dept., 2023).
Class 16 (May 23, 2024)
Readings
- Stephen P. Borgatti, et al. (2009), “Network Analysis in the Social Sciences”
alternative source: pre-copyedited manuscript of the article
- Elijah Meeks and Scott B. Weingart, “Introduction to Network Analysis and Representation” — click on the tabs for “centrality, ” “clustering coefficient,” etc. for brief interactive tutorials
Class 17 (May 28, 2024)
Readings
- Paola Pascual-Ferrá, Neil Alperstein, and Daniel J. Barnett, “Social Network Analysis of COVID-19 Public Discourse on Twitter: Implications for Risk Communication” (2020)
- Richard Jean So and Hoyt Long, “Network Analysis and the Sociology of Modernism” (2013) — read only pp. 147-149, 158-166
Class 18 (May 30, 2024)
Readings
- Christopher N. Warren et al., Six Degrees of Francis Bacon (2015)
- Optional: for a detailed explanation of methods used to create this project, see Christopher N. Warren et al., “Six Degrees of Francis Bacon: A Statistical Method for Reconstructing Large Historical Social Networks” (2016)
- Franco Moretti, “Network Theory, Plot Analysis” (2011) (Note: Because this essay in PDF format places its many social network graphs all at the end, a convenient way to read is to create and open two copies of the same essay, keeping one open to the graphs.)
Mapping
Class 19 (June 4, 2024)
Readings
- Franco Moretti, Graphs, Maps, Trees (2007), pp. 34-64
[Purchase this book, available at the UCEN bookstore] - Ian Gregory and David Cooper, “Geographical Technologies and the Interdisciplinary Study of Peoples and Cultures of the Past” (2013)
Class 20 (June 6, 2024) — Last Meeting of Course
Readings
- Student Presentations (presentations in class of final project proposals) (Note: the actual final project proposals must be submitted on the course Canvas site here by the end of June 11.)
(Due by June 11, 2024) — Final Assignment Due This Date (not a class meeting date)
A Note About Access to Reading Materials For This Course
There is one book to purchase for the course: Franco Moretti, Graphs, Maps, Trees: Abstract Models for a Literary History, Paperback ed (London: Verso, 2007), ISBN-13: 978-1844671854. (Available as physical book at UCEN Bookstore and in both physical and digital forms from online vendors; please acquire book as soon as possible, since readings are assigned from it beginning in Class 3.)
All other readings are online. Paywalled articles can be accessed over the UCSB network (or from off-campus by using the campus VPN (through the Ivanti Secure Access service, previously named Pulse) or the campus Library Proxy Server. You can also try to find open-access versions of paywalled materials using the Unpaywall extension for the Chrome or Firefox browsers. (Advice: It is a good idea to download materials as early as possible in case, for example, PDFs that are currently available open-access, on the open net, or through a UCSB Library digital database subscription later become inaccessible.)
Because so many readings are online (an increasingly prevalent trend in college courses), students will need to develop a method or workflow for themselves that optimizes their ability to study the materials. While everyone has their own personal preferences and technical constraints, the following guide includes suggested options for handling online materials:
Social Network Analysis