English 197 — Intro to DH (F 2022) – Schedule

Schedule for English 197 (F 2022)

Introduction to Digital Humanities

This is the main course website. There is also a course Canvas site for uploading assignments.

Introduction

Class 1 (Sept. 22, 2022)

Introduction to the course

Close vs. Distant Reading

Class 2 (Sept. 27, 2022)

Readings

Class 3 (Sept. 29, 2022)

Readings

  • Franco Moretti, Graphs, Maps, Trees (2007), pp. 1-33 Print book
    [Purchase this book, available at the UCEN bookstore]

Text Encoding

Class 4 (Oct. 4, 2022)

Readings

Text Analysis

Class 7 (Oct. 13, 2022)

Readings

Text Analysis (Topic Models)

Class 8 (Oct. 18, 2022)

Readings

Class 10 (Oct. 25, 2022)

Readings

Class 11 (Oct. 27, 2022)

Readings

  • Background Readings in Linguistics Theory
    • Ferdinand de Saussure, Course in General Linguistics (1959)  – 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 in GauchoSpace]

Text Analysis (Word Vectors)

Class 12 (Nov. 1, 2022)

Readings

  • Benjamin Schmidt, “Vector Space Models for the Digital Humanities” (2015)
  • Saptarashmi Bandyopadhyay et al., “Word Embedding Demo: Tutorial” (2022) — Note: The actual demo accompanying this tutorial about word embeddings (or word vectors) is assigned for the second part of Practicum 5.

Class 13 (Nov. 3, 2022)

Readings

AI (Large Language Models)

Social Network Analysis

Class 16 (Nov.15, 2022)

Readings

Class 18 (Nov. 22, 2022)

Readings

Mapping

Class 19 (Nov. 29, 2022)

Readings

Class 20 (Dec. 1, 2022)

Readings

  • Student Presentations (presentations of final project proposals due in final form on Dec. 6)

(Due by Dec. 6, 2022) — Final Assignment

Solo assignment icon Due March 14: Solo Assignment 4 — Essay About Project
20% of final grade

Each member of a team individually writes a three-page essay (approximately 900 words) that reflects critically on their team’s data narrative project. “Critically” means that the essay should identify both the strengths and problems of the specific data narrative, and possibly also those of data narratives in general.

The essay can begin with, or include, a description of the student’s team project and its essential message. But it must go beyond that to think critically about what works well and what doesn’t in the data narrative or in data narratives generally.

Conclude the essay with a paragraph offering a utopian vision of what the ideal version of the team data narrative would add if you had all the time and resources you needed.

Address the essay to a hypothetical general audience and not just “insiders” to our class who already know all the necessary context or information aobut your project. Include notes that cite any sources, borrowings, or quotations.

This is a solo writing assignment. Of course, teams will have already discussed their data narrative project together. But each team member must write an essay individually without borrowing directly from anyone else’s writing. It is fine, however, to draw on collective team discussion that has already occurred so long as there is a clear footnote or endnote crediting the team (e.g., “This idea comes from our team discussion,” or, “I borrow with variation an idea that came up in our team discussion”).

Grading Rubric

Submit the essay as a PDF file through the course Gauchospace site here.

Solo assignment icon Additional Solo Grade for Participation in Team Project and in Class Discussion
10% of final grade

The instructors will assign an additional 10% of the final grade based on their assessment of a student’s participation throughout the course in their team project (as witnessed in visible contributions to the final project or background contributions in a team’s shared drive) as well as in class discussion. Any student who participates equally in the team project and also speaks up during class discussion should be able to earn the full 10% of this grade.

A Note About Access to Reading Materials For This Course

Cover of Franco Moretti's Graphs, Maps, Trees

Cover of Franco Moretti’s Graphs, Maps, Trees

 

Manicule 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 at UCEN Bookstore; please acquire book as soon as possible, since readings are assigned from it beginning in Class 2.)

Manicule All other readings are online. Paywalled articles can be accessed over the UCSB network (or from off-campus by using the campus Pulse VPN service 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:

Guide to Downloading and Managing Online Readings

 

This is the main course website. There is also a course Canvas site for uploading assignments.
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