Schedule and Topics

Syllabus

The latest syllabus, including additional readings not listed below, is here: PDF

Schedule and Topics

  • Subject to change; this will be our most up-to-date schedule.
  • We will use bCourses to host files etc. and only enrolled students will have access.
  • For Thursday sessions, see lab and final project requirements for further details.
  • Optional materials (on bCourses) provide supplementary deep dives on related math and algorithms (with a particular focus on how certain lower-level things work before they are packaged away through APIs), designed either to refresh you on prerequisite concepts or to offer extensions to lecture topics, for those interested in learning more.

Week Humanistic Technical
1 operationalization featurized models
8/28 (Th) Prologue: Representing, Operationalizing, . . .

Primary readings the lecture draws on, optional but encouraged (see syllabus for additional readings):

  • Quist, “Laurelled Lives” (2017) [Demo]
  • Page et al., “The PageRank Citation Ranking: Bringing Order to the Web” (1999)
  • So, Redlining Culture (2020): chap. 3 (Recognition: Literary Distinction and Blackness)

Optional: math self-assessment (cf. Kun, A Programmer’s Introduction to Mathematics); Python self-assessment (cf. Walsh, Introduction to Cultural Analytics & Python)—see bCourses.

Act I. Termination and Indetermination
2 formalism and New Criticism word embeddings
9/2 (Tu) Lecture: Death of Theory
  • Eliot, “Tradition and Individual Talent—I” (1919)
  • Murphy, Probabilistic Machine Learning, book II. 32.1–4 (Representation learning)
  • Mikolov et al., “Distributed Representations of Words and Phrases and their Compositionality” (2013) [Demo: Word2Vec]

Optional: What’s the BPE tokenizer?

9/4 (Th) Annotation
  • Primer: reading, annotation, and passage analysis
  • Benj Pasek and Justin Paul, Dear Evan Hansen (2017)
9/5 (Fri) HW1 out (close reading paper)
3 formalism and narrative structure generative models
9/9 (Tu) Lecture: Death of Subjectivity
  • Adorno, Aesthetic Theory (1970): pp. 1–8; Piper, So, and Bamman, “Narrative Theory for Computational Narrative Understanding” (2021)
  • Murphy II. 20.1–20.4.1 (Generative models: an overview)
  • Vafa, Naidu, and Blei, “Text-Based Ideal Points” (2020) [Demo]

Optional: What’s in a recommendation system?

9/11 (Th) Quiz 1 (in class)
4 French structuralism sequence models
9/16 (Tu) Lecture: Death of the Author
  • Jakobson, “Closing Statement: Linguistics and Poetics” (1960)
  • Weatherby and Justie, “Indexical AI” (2022)
  • Murphy I. 15.1–3 (Neural sequence modeling)
9/18 (Th) Lab
5 deconstruction transformer blocks and residual stream
9/23 (Tu) Lecture: Interlude: Language Models for Cultural Analytics (I)
9/25 (Th) Lab
9/26 (Fri) HW 1 due (close reading); HW 2 spec out (workshop notebook)
6 structuralist analysis modeling and evaluation
9/30 (Tu) Lecture: Interlude: LMs for Cultural Analytics (II)

Thinking about “words”

  • Lucy et al., “Discovering Differences in the Representation of People using Contextualized Semantic Axes” (2022)
  • Wu and Smith, “Composition and Deformance: Measuring Imageability with a Text-to-Image Model” (2023)

Thinking about sequences

  • Classification: Guhr et al., “Making BERT Feel at Home: Modelling Domestic Space in 19th-Century British and Irish Fiction” (2025); Bamman et al., “On Classification with Large Language Models in Cultural Analytics” (2024)
  • Text re-usue: Walsh and Preus, “Not With a Bang But a Tweet: Democracy, Culture Wars, and the Memeification of T.S. Eliot” (2025); So et al., “Race, Writing, and Computation: Racial Difference and the US Novel, 1880-2000” (2019)

Misuses

  • Long and So, “Literary Pattern Recognition: Modernism between Close Reading and Machine Learning” (2016)
  • Chang et al., “Subversive Characters and Stereotyping Readers” (2024)
10/2 (Th) Quiz 2 (in class)
Act II. Being and Vectorizing
7 limits of critique diffusion models
10/7 (Tu) Lecture: Postcritique
  • Hayles, “Information or Noise? Economy of Explanation in Barthes’s S/Z and Shannon’s Information Theory” (1987) [cf. Derrida, “Force and Signification” (from Writing and Difference, 1961)]
  • Gius and Jacke, “Are Computational Literary Studies Structuralist?” (2022)
  • Murphy I. 4.7 (Frequentist Statistics)
10/9 (Th) Lab + lecture
  • Murphy I. 19.2 (Transfer learning)
  • Murphy I. 20.3 (Autoencoders)
10/10 (Fri) Project proposal due (MAX 1 p.)
8 Imagetext vision and language models
10/14 (Tu) Lecture: Imagetext
  • Mitchell, Picture Theory (1995): Introduction; chap. 1 (The pictorial turn)
  • Vilnis and McCallum, “Word Representations via Gaussian Embedding” (2015)
  • Radford et al., “Learning Transferable Visual Models From Natural Language Supervision” (2021)
10/16 (Th) Lab
9 time-image long-form video understanding
10/21 (Tu) Lecture: Time-Image
  • Ruhe et al., “Rolling Diffusion Models” (2024)
  • Deleuze, Cinema 2 (1989): chap. 2 (Recapitulation of images and signs)
  • Bertasius et al., “Is Space-Time Attention All You Need for Video Understanding?” (2021)
10/23 (Th) Workshop

Revivist demo notebooks; writing and presentation:

  • Sims, Park, and Bamman, “Literary Event Detection” (2019)
  • Bode, “Why You Can’t Model Away Bias” (2020)
  • Shechtman, “Command of Media’s Metaphors” (2021)
10 assemblage; relational forms, intersubjectivity mixture-of-experts; graphs, connotation frames
10/28 (Tu) Lecture: Assemblage
  • Deleuze and Guattari, A Thousand Plateaus (1987): chap. 6
  • Tsing, The Mushroom at the End of the World (2021): Part 1
  • Yu et al., “MMOE: Enhancing Multimodal Models with Mixtures of Multimodal Interaction Experts” (2024)
  • Demo: Sun et al., “video-SALMONN: Speech-enhanced Audio-Visual Large Language Models” (2024)
    • 10/30 (Th) Lecture: Relationality
    • Simondon, Individuation in Light of Notions of Form and Information (1964 [2021]): “Form and Matter”
    • Ferreira Da Silva, Unpayable Debt (2019): chap. 2 (the most perfect hallucination)
    • Stiennon et al., “Learning to Summarize with Human Feedback” (2020)
    • Demo: Antoniak et al., “Riveter: Measuring Power and Social Dynamics Between Entities” (2023); Bordes et al., “Translating Embeddings for Modeling Multi-relational Data” (2013)
    10/31 (Fri) HW 2 due (workshop notebook)
Act III. Everywhere and Nowhere
11 literary sociology scaling laws, alignment
11/4 (Tu) Seminar: Form and Scale
  • English and Underwood, “Shifting Scales” (2016)
  • Klein, “Dimensions of Scale” (2020)
  • Muennighoff et al., “s1: Simple Test-Time Scaling” (2025)
    • 11/6 (Th) Lab
    Lecture on demand: Form and Ideology
    • Jameson, The Political Unconscious (1994): chap. 1 (On Interpretation)
    • Clough, The User Unconscious (2018): “The Datalogical Turn”
    • Ziems et al., “Can Large Language Models Transform Computational Social Science?” (2024)
    11/7 (Fri) Project mid-term report due
12 – –
11/11 (Tu) (no class—academic holiday)
11/13 (Th) Lab
13 situated knowledge long-context models, knowledge retrieval
11/18 (Tu) Lecture: Form and Context
  • Silverstein, Language in Culture (2022): Introduction; chap. 8 (“Knowledge”)
  • Fish, “Is There a Text in This Class?” (1995)
  • Jurgens et al., “Your Spouse Needs Professional Help” (2023)
11/20 (Th) Seminar (TBD)
  • Chevalier et al., “Adapting Language Models to Compress Contexts” (2023)
  • Khanuja et al., “An Image Speaks a Thousand Words, but Can Everyone Listen?” (2024)
  • Edge et al., “From Local to Global: A Graph RAG Approach to Query-Focused Summarization” (2024)
14 (Thanksgiving)
15 modernity validity
12/2 (Tu) Epilogue: What Is Cultural Analytics?
  • Park and Aronson, Maybe Happy Ending (2025)
  • Mbembe, “The Universal Right to Breathe” (2021)
12/4 (Th) Project presentation (in class)
16 (RRR)
12/12 (Fri) Project final report due

(last updated: September 22, 2025)