Power and Authority on the Early American Frontier: Explorations with Text Analysis | Fall 2019 Syllabus

Course Description:

This is an upper division Digital Humanities course that teaches text analysis, employing both user friendly tools and Python. We apply these techniques to study the history of Native- and Euro- American interactions in the present-day Midwest between 1776 and 1820.

What did the Native American communities think, feel, and do in response to Euro-American incursion and settlement during and after the Revolutionary War? Who held power and of what kind in the late eighteenth century? How do we know? This course explores these questions and more using computational text analysis methods to understand the history and legacy of settler colonialism. In this course, you will learn how to structure data to prepare it for digital analysis using a variety of methods including word frequency, word distinctiveness, collocations, topic modeling, and comparative corpus linguistics. In addition, you will learn how to ask computationally tractable questions, detect bias, craft evidence-based arguments, and determine the limits of digital research methods.

While this course applies these methods to historical research, the skills you will learn transfer to social media analysis, data journalism, marketing analysis, qualitative business analytics, and more.

Animating Questions:

Who was responsible for shaping events in the American territories?
Who held power? What kind of power? How do we know?
What did authority mean in the backcountry? What were the relationships between power, authority, position, and gender?
How did Native American leaders perceive the British, French, and Americans who came into their territories?
How did Native American communities relate to and communicate with one another?
What are the possibilities and limits of computational text analysis, particularly when used to understand eighteenth-century Native people and communities?

Learning Outcomes:

This course will guide you in developing fundamental digital research skills, including how to structure data, use text mining techniques to extract data from unstructured and semi-structured texts, and how to use text analysis methods to explore qualitative data to answer historical questions.

This course will help you develop critical thinking skills, such as:

Asking good questions
Reading to identify and understand an author’s argument
Making connections between ideas, diverse sources, and perspectives
Detecting bias
Crafting evidence-based arguments
Deciding where the limits of knowledge lie

Search:

Date	Reading 1	Reading 2	In-Class Activities	Assignments
10/2/2019	Listen to Susan Sleeper Smith, Ben Franklin’s World, podcast, episode 223, (January 28, 2019). (1h 6min).		Attendance Introduction to the course, materials, and requirements Discussion of Sleeper-Smith’s interview Introduction to Voyant Tools Primary source analysis
10/9/2019	Daniel K. Richter, Facing East from Indian Country, chapters 1-2.	Brandon Walsh and Sarah Horowitz, Introduction to Text Analysis: A Coursebook. Read: Introduction, Issues in Digital Text Analysis, Close Reading, Data Cleaning, Cyborg Readers	Mini-Lecture on context Discuss readings Manually transcribe handwritten documents Basic text analysis with Voyant Tools Tutorial Topic & team selection Discuss documents for the project’s corpus
10/16/2019	Richter, chapters 3-4	Ashley Glassburn, “Settler Standpoints,” WMQ 76, no. 3 (July 2019): 399-406.	Analyze model argument based on word frequency analysis: Stéfan Sinclair & Geoffrey Rockwell, “Now Analyze That!” Hermeneutica (2016). Quiz 1: Word frequency analysis Discuss readings Intermediate Text Analysis Tutorial: TF-IDF & Collocations	Project 1 Parameters: Research Questions, Bibliography & Primary Sources
10/23/2019	Richter, chapters 5-6.	Colin Calloway, Pen & Ink Witchcraft, Prologue & chapter 1.	Model Analysis Discuss readings NER Analysis with Recogito Install Python 3, Jupyter Notebooks, Pandas, etc. & VADER Sentiment Analysis package.	Individual Annotated Bibliography Applying text analysis methods to Project 1 - analysis first draft
10/30/2019	Calloway, chapter 2	Introduction to Text Analysis: A Coursebook. Read: Sentiment Analysis	Project 1 Lightning Round Discuss Readings Sentiment analysis with Python 3	Project 1 Teammate & Self Evaluation
11/6/2019	Calloway, chapter 3	Stefan Evert, “Corpora & Collocations,” sections 1-4.	Discuss readings The math behind collocation analysis Collocations with Python & NLTK Select Project 2 topics & teams Midterm course eval & instructor feedback	In-class: Project 2 Topic & Team Selection
11/13/2019	Calloway, chapters 4-5	Introduction to Text Analysis: A Coursebook. Read: Topic Modeling & Classifiers	Quiz 2: NER, sentiment analysis & collocations Model Analysis: “Topic Modeling the Territorial Papers of the United States.” Discuss readings Install MALLET	Project 2 Parameters: Research Questions, Bibliography & Primary Sources
11/20/2019	Calloway, chapter 6	Ted Underwood, "Topic Modeling Made Just Simple Enough" Robert K. Nelson, "Of Monsters, Men & Topic Modeling"	Model Analysis: Robert K. Nelson and Digital Scholarship Lab, University of Richmond, “Mining the Dispatch,” 2011. Discuss readings Project 2 Work Time	Individual Annotated Bibliography
11/27/2019	Calloway, chapter 7		Discuss reading Quiz 3: Topic Modeling Work on Project 2	Applying text analysis methods to Project 2 - analysis first draft
12/4/2019	Heidi Bohaker, “Indigenous Histories and Archival Media in the Early Modern Great Lakes,” in Colonial Mediascapes: Sensory Worlds of the Early Americas, edited by Matt Cohen and Jeffrey Glover (University of Nebraska Press, 2014), 99-140.		Discuss Bohaker and the limits of text analysis Practice presentations Class wrap-up	In class: Project presentation peer review form
12/13/2019			Final Project Presentations	Final project Individual Reflection

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Tags : Course, Native American History, Syllabus, Text Analysis

Ashley R. Sanders, Ph.D.