Tuesday + Thursday, 9:30-10:45, 243 Kauke // Dr. Jacob Heil, 158D Andrews Library

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Week_00: Establishing our workspaces, getting started.

For class today:

Week_01: Defining humanistic inquiry

This week we’ll continue to locate the humanities in the “digital humanities,” we’ll look at example DH projects, and we will work on carving out our own space on the internet.

Week_02: Defining DH Projects

We’ll look at more DH projects and develop a framework for thinking about their core components. We’ll also share the first parts of our website projects, which are due this week.

Week_03: DH Datasets

Continuing to think about “digital” “humanistic inquiry,” we will talk about what comprises a DH dataset, we’ll find some, and we’ll begin to explore what we can do with them.

Week_04: Text Analysis: 1

We’ll look at some DH Projects of your choosing. We will also do some low-barrier, web-based text analysis using Voyant, about which you can learn more here.

Week_05: Curating a Humanities Dataset

Now that we’ve seen and done work with datasets, we will begin to make and clean our own. Drop Date is 2/22.

Week_06: Telling Robots What to Do: 1

Our first foray into object-oriented programming with python. We’ll read some of the scripts that run our Poembot and we’ll discern how the programs talk to the datasets we’ve created.

Week_07: Critical Making and Physical Computing in DH

We will read about critical making and physical computing in DH, we’ll engage some some of both as we assemble our Poembot for Poetry Month. We’ll pause for a midterm assessment and reflection. Also, your report on a low-barrier DH Tool is due this week.



Week_10: Telling Robots What to Do: 2

Building on the work we’ve done in Python, we’ll more deeply explore the relationships between scripts and datasets. We’ll build a bot and we’ll think about why one might build bots.

Week_11: Reading Machines

We’ll expand the sophistication of the algorithms we’re using to create bots that process and re-present textual datasets. How to bots “read” and “summarize”?

Week_12: Text Analysis: 2, Algorithmic Text Analysis with Topic Modeling

After wrapping up discussions of Bots, we will explore topic modeling by interrogating the algorithms behind this kind of natural language processing, reflecting on its limits, creating some models of our own, and interpreting them.

Week_13: Visualizing Humanities Data More Topic Models and Intro to Stylometry

Given our semester, we’ll stay in macroanalysis of texts for this week so that we might continue to process more texts, differently. We’ll process humanities data in yet another way by exploring visualization tools (and discussing how some of the tools we’ve already used can be viz tools).

Week_14: Text Analysis: 3, Algorithmic Text Analysis with Stylometry

We’ll use Stylo, a tool that allows the Statistical Program R to process textual data for stylometric similarities and difference. Think of authorship attribution studies: are Shakespeare’s plays actually written by Christopher Marlowe?

Week_15: Save Your Work!

Our last week. We’ll tie up the loose ends, we’ll devote some in-class time to working on final projects, and we’ll present our final projects and part 2 of our Websites.

Booking Meetings

Course Archive: 2017

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An Introduction to Digital Humanities by Jacob Heil is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.