TXTDS 267 A: Data Science and the Humanities

ENGL/TXTDS 267: Introduction to Data Science in the Humanities

Spring 2025 | T/Th 1:30 PM - 3:20 PM | Condon Hall 125

Instructor: Gian Duri Rominger (gromin@uw.edu)

Office Hours: Th 12-1 PM (GWN M225)

General Overview

Course Description

Do humanistic questions have a place in the field of data science? Conversely, are methods from data science useful for the study of literary classics, works of art, or historical debates? And how can humanities approaches help us address issues of bias and exclusion in an increasingly technology-driven world? This course tackles such broad issues while offering an introduction to a range of approaches and methodologies within the growing field of humanities data science. Topics will include text digitization, digital archiving, data visualization, modeling, and text analysis. During the course, we will work with and analyze a broad range of digital resources, including online libraries, digital editions, cultural datasets, data visualization platforms, text analysis packages, and creative projects. The final assignment will involve creating a digital version of a text or curating an original dataset related to cultural artifact(s) and writing an analysis paper.

This syllabus is based on one designed by Anna Preus, with additional inspiration taken from Grant Wythoff.

Learning Objectives

• Demonstrate an understanding of the structures and functions of digital tools and examine the ways they have been applied to the preservation and study of cultural artifacts.
• Develop skills in data manipulation and make use of various methods of close and distant analysis to enunciate arguments about cultural artifacts and historical trends.
• Consider how humanistic questions apply to systems for producing and analyzing data.
• Examine how systems of power including capitalism, racism, white supremacy, sexism, heteronormativity, ableism, transphobia, colonialism, and imperialism impact the production, dissemination, and valuation of information online and in digital forms.
• Amplify alternative methodologies and ways of knowing, listening and learning about the past and present, the local and the global, and consider how these ways of knowing apply to the digital realm.

Required Texts

All required readings will be available on Canvas or linked through the UW library catalog.

Required Materials

Please bring a computer to each class. If you do not have access to a computer you can bring to class, you can check one out through the Student Technology Loan Program. If you have concerns about technology access for this class, please let me know via email or in office hours.

Contact and Office Hours

I will be happy to address brief questions through Canvas messages.  If you have more involved questions, I will be glad to speak to you in office hours or by appointment.

• Office Hours: Th 12-1 PM (GWN M225)

Assignments

• Class Participation (15%)
• Technical Assignments (20%)
• Digital Resource Analysis Essay (20%)
• Note-Taking Assignment (5%)
• Final Project Proposal (10%)
• Final Project (30%)

Participation (15% – ongoing): It is important that you complete assigned readings by the day they are listed on the schedule and come to class ready to engage constructively with the material alongside your classmates. I will also assign in-class responses and activities, which  may take the form of group discussions, written responses, interaction with digital tools, and practical skill applications. These activities are graded only for completion. They will be conducted in-class and cannot be made up.

Technical Assignments (20% – due April 21 and May 12): There will be two brief technical assignments  during the quarter, related to text digitization and data visualization. Each assignment is worth 10% of your overall grade. Technical assignments will be submitted on Canvas.

Note-Taking Assignment (5% – sign up for a class session): You will need to sign up for one class during the quarter where you will be a designated note-taker. The 1-2 people in this role on a day will take notes on the content covered and post them to the “Class Notes” page as well as submitting them on Canvas. Notes should be posted and submitted within 24 hours of the end of the class they cover so that classmates who have missed the class will be able to access them before the next class. We will begin the note-taking assignment in week 2, and I will send out a sign up sheet after class in week 1.

Digital Resource Analysis (20% – due May 5): This essay should offer discussion and analysis of one of the digital resources posted on Canvas.  You may focus on one aspect of the resource—for example an edition of a text within an online archive—or you may focus on the resource as a whole, but either way your essay should analyze and critically respond to the choices the creator(s) made in representing the material in digital form and the implications of those choices. Length: ~1,000 words.

Final Project Proposal (10% – due May 20): The Final Project Proposal should identify the focus of your project, identify key questions you hope to answer or address, and offer a plan for how you will complete the project. Length: ~500 words.

Final Project (30% – due June 4): For your final project you will have two options 1) create or curate a dataset focused on a cultural artifact or artifacts, or 2) create a digital version or interpretation of a cultural artifact or artifacts. Whichever option you choose, you will write a paper offering interpretation and analysis of your dataset or digital artifact. Length: ~1,250 words.

Grading of Written Work

All papers should be word-processed, double-spaced in 12-point font (preferably Times New Roman), and submitted via Canvas. Please use the Chicago Manual of Style, 17th ed., for formatting source citations (notes and bibliography) and general formatting.

An “A” paper directly addresses the prompt and makes a meaningful interpretive claim that is relevant to conversations about humanities data science. The writer includes an original claim that is backed up by defined points that are rooted in analysis of concrete evidence. It moves beyond material covered during class discussions. The writing is clear and conveys the author’s points effectively.

 A “B” paper addresses the prompt and makes an interpretive claim about a literary work, but the claim may be overly broad or narrow, or the author may not adequately demonstrate why it matters to conversations in humanities data science. The paper presents a solid argument and evidence but may lack specificity or stray from the primary claim. It mostly moves beyond material covered in class discussions. The writing is generally clear but may contain errors that interfere with its readability.

 A “C” paper to some degree addresses the prompt and demonstrates a generally good grasp of the material, but its analysis may be weakened by problems with organization or clarity. The paper makes good points and demonstrates an understanding of its subject, but it is not well organized or backed up by close examination of that subject. It tends to present summary instead of analysis and the argument may not be backed up with evidence. The paper may contain errors that interfere with its readability.

 A “D” paper attempts to address a reasonable subject but lacks an original thesis. The paper does not make a clear point or does not have a clear argument, and the reader may be confused about what the essay is trying to accomplish. The paper may include misreadings, or grammatical errors that obscure meaning. Like the C paper, it tends to present summary in the place of analysis and may contain errors that interfere with its readability

Grade Scale

Schedule of Readings & Assignments

Please note: This is a tentative course calendar and is subject to change.

Introduction: The Humanities & Data Science?

Week 1

T March 26

Introduction to the course

Th March 28

• Rens Bod, A New History of the Humanities (Oxford: Oxford Univ. Press, 2014), Introduction: “The Quest for Principles and Patterns.”

Exercise:

• Review list of departments and programs classified as Humanities and Social Sciences at UW

Week 2

T April 2

• Barbara Herrnstein Smith, “What Was Close Reading? A Century of Method in Literary Studies,” Minnesota Review 87 (2016): 57–75.
• Brad Pasanek, “Extreme Reading: Josephine Miles and the Scale of the Pre-Digital Digital Humanities,” ELH86, no. 2 (2019): 355–85.
• Harvard libguide on close and distant reading (https://guides.library.harvard.edu/literature/closereading)

Text Digitization

Th April 4

• Brewster Kahle, “Universal Access to All Knowledge” [PDF]

Digital Editing

Week 3

T April 9

• Julia Flanders, Syd Bauman, Sarah Connell, “Text encoding” (p. 105-116) [PDF]

Th April 11

• Amanda Gailey, “A Case for Heavy Editing: The Example of Race and Children’s Literature in the Gilded Age” (125-136)
• Katie Rawson, and Trevor Muñoz, “Against Cleaning”
• Emily Dickinson, "Hope is the thing with Feathers," [link] [PDF]
• Dickinson, "Because I could not stop for Death" [link] [PDF]

Metadata

Week 4

T April 16

• Kimberley Christen, “Relationships Not Records: Digital Heritage and the Ethics of Sharing Indigenous Knowledge Online”
• Aashna Sheth, “Summarizing America: The Impact of Metadata on Historical Discovery” [link]

Th April 18

• CLASS CANCELLED

 ~Technical assignment #1 due Sunday, April 21st via Canvas~

Non-Anglophone Texts

Week 5

T April 23

• Quinn Dombrowski and Patrick Burns. “Language is not a Default Setting: Countering
  Digital Humanities’ English Problem.”

Digital Archives

      Th April 25

• Roopika Risam, “Colonial Violence and the Postcolonial Digital Archive” from New Digital Worlds (p. 47-61)
• Laura C. Mandell, "Gendering Digital Literary History" [PDF]

Data Manipulation & Visualization

Week 6

T April 30

• Melanie Walsh, “Anatomy of a Python Script” from Introduction to Cultural Analytics and Python [link] [PDF]
• Walsh, “Python Variables” [link],
• Walsh, “Python Data Types” [link]

Th May 2

• D'Ignazio and Klein, “The Numbers Don’t Speak for Themselves” in Data Feminism [link] [PDF]
• Allen Downey, “The Way of the Program” from Think Python [link] [PDF]
• Melanie Walsh, “Data Analysis: Pandas Basics – Part 1” [link]

~Analysis of a Digital Resource due Sunday, April 28th via Canvas~

Week 7

T May 7

• Ruha Benjamin, “Default Discrimination: is the Glitch Systemic” from Race After Technology: Abolitionist Tools for the New Jim Code [PDF]
• Melanie Walsh, “Data Analysis: Pandas Basics – Part 2” [link]

Text Analysis & Computational Literary Studies

Th May 9

• Ted Underwood, “Seven ways humanists are using computers to understand text” [link] [PDF]
• Melanie Walsh, “Python String Methods” [link], “Comparisons and Conditionals”[link], “Python Lists and Loops” [link]

~Technical Assignment #2 due Sunday, May 12th via Canvas~

Week 8

T May 14

• Melanie Walsh, “Sentiment Analysis” [link]
• Kate Chopin, “The Story of an Hour” [link]

Modeling, ML

Th May 16

• Megan R. Brett, “Topic Modeling: A Basic Introduction” [link]
• Lisa Rhody, “Topic Modeling and Figurative Language” (2012) for an overview of topic modeling

Week 9

~Final project proposal and data plan due Monday, May 20th~

T May 21

• Matthew Jockers and David Mimno, “Significant Themes in 19th Century Literature” [link]
• Hoyt Long and Richard Jean So, “Literary Pattern Recognition: Modernism between Close Reading and Machine Learning” [PDF]

Th May 23

• Ted Underwood, “The Life Cycles of Genres” [PDF]
• Paul Vierthaler, “Fiction and History: Polarity and Stylistic Gradience in Late Imperial Chinese Literature"

Prospects

Week 10

T May 28

• Nan Z. Da, “The Computational Case against Computational Literary Studies” [PDF] [Pages 600-605]

Th May 30

• Eun Seo Jo and Timnit Gebru, “Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning,” Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, (January 27, 2020), 306–16.
• Miriam Posner, “What’s Next: The Radical, Unrealized Potential of Digital Humanities” (2016)

Week 11: Final Exam Week

~Final Project and Paper due Tuesday, June 4th via Canvas~

Course Guidelines and Policies

Academic Integrity

The University of Washington Student Conduct Code (WAC 478-121) defines prohibited academic and behavioral conduct and describes how the University holds students accountable as they pursue their academic goals. More information can be found online at: https://www.washington.edu/studentconduct/

The University takes academic integrity very seriously. Academic integrity is part of your responsibility to our shared learning community. If you’re uncertain about whether something constitutes academic misconduct, don’t hesitate to ask me. I am willing to discuss any questions you might have.

Acts of academic misconduct may include but are not limited to:

• Cheating (working collaboratively on quizzes/exams and discussion submissions, sharing answers, and previewing quizzes/exams)
• Plagiarism (representing the work of others as your own without giving appropriate credit to the original author(s))
• Unauthorized collaboration (working with each other on assignments)

Concerns about these or other behaviors prohibited by the Student Conduct Code will be referred to the appropriate campus office for investigation and resolution. Infractions will result in a grade of ‘x’ and be referred to the Dean's Representative for Academic Conduct.

Access and Accommodations

Your experience in this class is important to me. The University of Washington is committed to creating inclusive and accessible learning environments consistent with federal and state law. If you have already established accommodations with Disability Resources for Students (DRS), please activate your accommodations via myDRS so we can discuss how they will be implemented in this course. If you have not yet established services through DRS, but have a temporary health condition or permanent disability that requires accommodations (conditions include but not limited to; mental health, attention-related, learning, vision, hearing, physical or health impacts), contact DRS directly to set up an Access Plan. DRS facilitates the interactive process that establishes reasonable accommodations. Contact DRS at disability.uw.edu.

Mental Health Resources

The University of Washington offers a range of resources related to mental health and wellbeing. You can find information on available resources—which include 24/7 confidential mental health and crisis intervention support, options for ongoing individual and group therapy, one-time workshops, and links to off-campus resources—here: https://wellbeing.uw.edu/topic/mental-health/.

Religious Accommodation

Washington state law requires that UW develop a policy for accommodation of student absences or significant hardship due to reasons of faith or conscience, or for organized religious activities. The UW’s policy, including more information about how to request an accommodation, is available at Religious Accommodations Policy (https://registrar.washington.edu/staffandfaculty/religious-accommodations-policy/). Accommodations must be requested within the first two weeks of this course using the Religious Accommodations Request form (https://registrar.washington.edu/students/religious-accommodations-request/).

Technology

Please use electronic devices in class only to support your participation in class activities. Use of devices for other purposes (emailing, social media, etc.) may reduce your participation grade.

Use of large language model-based chatbots such as ChatGPT can be fun and occasionally even helpful, but regular use subverts the fundamental goals of this course, i.e. the development of your own knowledge and analytical skills. Any use of such programs or other implementations of generative LLMs is prohibited in written work you submit for this course. Such use constitutes academic misconduct and will be dealt with as such.

Safety & Basic Needs Security

Preventing violence is a shared responsibility in which everyone at the UW plays apart. Call SafeCampus at 206-685-7233 anytime – no matter where you work or study – to anonymously discuss safety and well-being concerns for yourself or others. SafeCampus’s team of caring professionals will provide individualized support, while discussing short- and long-term solutions and connecting you with additional resources when requested: www.washington.edu/safecampus

If you are facing challenges affording groceries or accessing sufficient food, or if you are lacking a safe and stable place to live, please reach out for support. The University offers food assistance through a range of resources associated with the “Any Hungry Husky” program. You can order food online through the UW Food Pantry, apply forEmergency Food Assistance, find out about low-cost food available through The Bean Basket, or apply for emergency aid more broadly. A list of off-campus resources, including housing resources, is also available. If you feel that issues of housing or food security may affect your performance in this course, please come talk to me if you feel comfortable doing so.

Sex- and Gender-based Violence, Harassment, and Discrimination

The UW, through numerous policies, prohibits sex- and gender-based violence, harassment, and discrimination and expects students, faculty, and staff to act professionally and respectfully in all work, learning, and research environments.

For support, resources, and reporting options related to sex- and gender-based violence, harassment, or discrimination, refer to the UW Title IX’s website, specifically the Know Your Rights & Resources guide. Should you wish to make the Office of the Office of the Title IX Coordinator aware of a Title IX concern, visit the Make a Title IX Report webpage. 

Please know that if you choose to disclose information to me about sex- or gender-based violence, harassment, or discrimination, I will connect you (or the person who experienced the conduct) with resources and individuals who can best provide support and options. You can also access additional resources directly:

• You can request anonymous support, fromSafeCampus 
• You can request confidential support, from aconfidential advocate.
• If you know you want to submit a formal complaint, contact theCivil Rights Investigation Office.

Please note that some senior leaders and other specified employees have been identified as Officials Required to Report. If an Official Required to Report learns of possible sex- or gender-based violence, harassment, or discrimination they are required to contact the Office of the Title IX Coordinator and report all the details they have in order to ensure that the person who experienced harm is offered support and reporting options.  

Writing and Academic Support

Improving your writing is hard, but it is not something you need to take on alone. The Odegaard Writing and Research Center and CLUE Study Center offer great options for writing tutoring and support. You can schedule an appointment to talk with someone at any point in your writing process, whether you’re generating ideas, conducting research, composing a draft, incorporating feedback, or even proofreading.

Late Work

All assignments should be submitted on Canvas by the end of the day they are listed on the syllabus. Submitting late work is strongly discouraged, but if you have extenuating circumstances, please contact me so we can discuss it. In general, late work will be graded for 75% credit.