Schedule

Flexbility

I am committed to a flexible schedule that meets your learning goals. You will see that I provide an outline for the semester, but I expect the precise readings to evolve as the semester develops. Indeed, one of your assignments will require each of you to take the lead in discussion for one week, which may involve adjusting that week’s readings. Our topic for the last week of class will be decided by vote.

In summary: the schedule below may change, so check it before beginning a week’s readings. I will commit to making any final edits for the next Thursday by the end of day on the previous Thursday (essentially, I reserve the right to make some tweaks immediately after class). For you, that means you need to think well ahead of time about any adjustments you want to make during your week, so that I can adjust the schedule in time.

Reading the Schedule

Each week’s class will blend discussion of assigned readings with hands-on practicum in a given method of data analysis within the R programming environment. At the end of each session, you will be given practice exercises for developing your proficiency with the week’s methods. In reading the schedule for any particular week, then,

  1. Core Readings are the articles, books, or web resources you are responsible for reviewing before class.
  2. Penumbral Readings are pieces pertinent to the week’s topic that will expand your understanding if you are so inclined (plus they’re good places to start additional research for your Notebooks and final papers). I would encourage you to choose one Penumbral reading each week that looks interesting and at least browse it.
  3. Dependencies outline the applications, packages, or other software you should install, any datasets you should download, and any technical tutorials you should complete before class.
  4. Practicums describe the technical elements we will work on in class.
  5. Exercises describe resources that will be useful as you complete your practice exercises and problem sets following class. If a specific outcome is not outlined, you should complete your exercises in R or RMD files for submission and/or later in-class reference. We will discuss how to do this in the first week of class, so do not worry if these letters mean nothing to you now.

Schedule

Readings not freely available online are available in a password-protect, zipped course packet. I will give out the password in class on day 1.

Week 1 %>% January 12 %>% What Is HDA and What Might It Be?

Core Readings:

The articles in Debates in the Digital Humanities 2016‘s “Forum: Text Analysis at Scale”. Important Note: I realize this looks like a crazy-long first-day assignment, but these are all position papers and each the length of short blog posts. It adds up to about one typical article’s length of brilliant thoughts that should give us much to discuss.

Penumbral Readings:

Dependencies: A text editor with full regular expression capabilities.

Practicum: regular expressions

Exercises: RegEx problem sets (available through course website)

Week 2 %>% January 19 %>% Histories

Core Readings:

  • Louis T. Milic, “The Next Step,” Computers and the Humanities 1.1. (1966)
  • Roberto Busa, “Why a Computer Can Do So Little,” ALLC Bulletin 4.1 (1976)
  • Yohei Igarashi, “Statistical Analysis at the Birth of Close Reading,” New Literary History 46.3 (2015)
  • Cameron Blevins, “Digital History’s Perpetual Future Tense,” Debates in the Digital Humanities 2016

Penumbral Readings:

Dependencies:

  • Install RStudio on your computer. Note that on some systems, this also requires you to install R itself. Please attempt this early in the week so that we can help you if anything goes awry.
  • If you’re feeling ambitious, work through Taylor Arnold and Lauren Tilton’s “Basic Text Processing In R” at the Programming Historian and browse Lincoln Mullen’s “Introduction” to his book-in-progress, Digital History Methods in R. We will use Mullen’s exercises throughout the semester; hereafter his book is designated as DHMR. To follow along with much of DHMR, you will need Mullen’s data, which he provides in the book’s Github repository.

Practicum: GrammaR

Exercises:

Week 3 %>% January 26 %>% Humanistic Data

Core Readings:

Penumbral Readings:

Dependencies: Install the ‘tidytext’ and ‘tidyverse’ R packages

Practicum: Data frames and tibbles

Exercises:

  • DHMR, “Working with Data” sections
  • R For Data Science (hereafter RDS), “Data Transformation” and “Exploratory Data Analysis”

Week 4 %>% February 2 %>% Exploratory Data Analysis

Core Readings:

Penumbral Readings:

  • John T. Behrens, “Principles and Procedures of Exploratory Data Analysis,” Psychological Methods 2.2 (1997)
  • Bryan Santin, Daniel Murphy, and Matthew Wilkens, “Is or Are: The ‘United States’ in Nineteenth-Century Print Culture,” American Quarterly 68.1 (March 2016)
  • Sarah Wilson, “Black Folk by the Numbers: Quantification in Du Bois,” American Literary History 28.1 (2016)

Dependencies: Install the ‘dplyr’ R package

Practicum: More work with tabular data

Exercises:

  • RDS, “Tibbles,” “Data Import,” and “Tidy Data”

Week 5 %>% February 9 %>% Snow Day

Week 6 %>% February 16 %>% Visualization

Discussion Leader: Matthew Hitchcock

Core Readings:

Penumbral Readings:

Dependencies: Install the ‘ggplot2’ R package

Practicum: The plots thicken

Exercises:

  • DHMR, “Plotting” and “Interactive Plotting”
  • RDS, “Data Visualization”

Week 7 %>% February 23 %>% Modeling

Discussion Leader: Gregory Palermo

Core Readings:

  • Anna Lowenhaupt Tsing, “On Nonscalability: The Living World Is Not Amenable to Precision-Nested Scales,” Common Knowledge 18.3 (2012)
  • Andrew Piper, “Novel Devotions: Conversional Reading, Computational Modeling, and the Modern Novel,” New Literary History 46.1 (2015)
  • Julia Flanders and Fotis Jannidis, “Data Modeling,” A New Companion to the Digital Humanities (Wiley Blackwell, 2016).

Penumbral Readings:

Practicum: Text analysis (led by Fitz)

Week 8 %>% March 2 %>% Topic Models

Core Readings:

Penumbral Readings:

Dependencies: Install ‘mallet’ R package

Practicum: Topic modeling with RMallet

Exercises:

  • DHMR, “Topic Modeling”

Spring Break

Week 9 %>% March 16 %>% Mapping

Discussion Leader: Lara Rose Roberts

Required Reading:

Penumbral Readings:

  • Richard White, “What Is Spatial History?” (1 February 2010)
  • Matthew Wilkens, “The Geographic Imagination of Civil War-Era American Fiction,” American Literary History 25.4 (2013)

Dependencies: Install the ‘ggmap’ R packages

Practicum: Mapping in R

Exercises:

  • DHMR, “Mapping”

Week 10 %>% March 23 %>% Vector Space Models

Discussion Leader: Thanasis Kinias

Core Readings:

Penumbral Readings:

Dependencies: Install the ‘wordVectors’ R package

Practicum: word2vec

Week 11 %>% March 30 %>% Classifying and Clustering

Discussion Leader: Cara Messina

Required Reading:

Penumbral Readings:

Week 12 %>% April 6 %>% Working groups

Prof. Cordell away for Rhode Island Humanities Festival

Week 13 %>% April 13 %>% Ludic Data Analysis

Discussion Leader: David Medina

Core Readings:

  • Stephen Ramsay, Reading Machines, University of Illinois Press (2011)

Penumbral Readings:

Practicum: Screwing around with data