TXTDS 267 A: Data Science and the Humanities

Autumn 2022
MW 10:30am - 12:20pm / CDH 110B
Section Type:
Joint Sections:
ENGL 267 A
Anna Preus
Syllabus Description (from Canvas):

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

Autumn 2022 | M/W 10:30-12:20 | Condon Hall 110B

Instructor: Anna Preus (apreus@uw.edu)

Office Hours: Tue. 10:30-11:30 (on Zoom) / Wed. 12:30-1:30 (in MGH 076)

Class JupyterHub>>

View syllabus on Google Docs >>

View class notes page >>


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, famous 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 data bias, text digitization, digital archiving, data visualization, modeling, and computational analysis. During the course, we will work with and analyze a broad range of digital resources, including online libraries, digital editions, data visualization platforms, text analysis packages, and creative projects. We will use and analyze these digital tools and work with datasets. The final project will involve conducting an original analysis of a dataset using digital tools. This course will take place in person. 

Syllabus designed in collaboration with Rachel Yim-Schlotfeldt and Nikita Willeford-Kastrinos.


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, collecting, storing, 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.


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.

Materials for in-class technical workshops will be available on Google Drive: https://drive.google.com/drive/folders/1V89XsSBmO01nZ145yNXbBqxDhT_0IO-P?usp=sharing 


Assignments and Grading

  • Class Participation (10%)
  • In-Class Responses and Activities (5%)
  • Digital Resource Responses [3 required] (15%)
  • Note-Taking Assignment (5%)
  • Digital Resource Analysis (25%)
  • Final Project
    • Topic Proposal and Data Plan (10%)
    • Dataset or Digital Resource (10%)
    • Findings and Analysis Paper (20%)


Participation (10%--ongoing)

Please 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. Contributing to in-class discussions is encouraged, but it is not the only way to earn a strong participation grade. Many types of engagement can contribute positively to your grade, including coming to class on time and prepared, taking part in in-class activities and group work, and attending office hours.

In-Class Responses and Activities (5%--ongoing)

Throughout the quarter, I will assign in-class responses and activities that pertain to our weekly topic. These may take the form of group discussions, written responses, interaction with digital tools, or practical skill applications. These will be conducted in-class and cannot be made up.

Digital Resource Responses (15%--complete 3 anytime)

You are required to submit 3 short responses to digital resources included on the syllabus/discussed in class. Starting in week 3, each week I will post a list of digital tools/resources related to the topics we're covering and a prompt for those who want to submit a response. You may choose any weeks to submit responses, but I recommend doing it earlier in the quarter, before you are working on your final project.  Responses should be 200-300 words and 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 2-3 people in this role on a given day will take notes on the content covered and post them to the “Class Notes” page. Notes should be posted 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 3, and I will send out a sign up sheet in week 2.

Digital Resource Analysis (25%--due 10/28)

This paper should offer discussion and analysis of one of the digital resources listed on the syllabus. 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 paper 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. Your paper must engage at least one of the readings from the course. Required length: 1,000 to 1,250 words.

Final Project 

Your final project asks you to form and pursue a humanistic question through the creation of a dataset or digital resource and to write a paper that discusses your methods and analyzes your results. The Final Project will consist of three main parts:

  • The Project Proposal and Data Plan (10%--due 11/18): This first portion of the Final Project should include a Project Proposal section of roughly one page in length that defines your project’s topic area, poses a central question, and drafts a tentative plan for utilizing a dataset or creating a digital resource to answer that question. The Data Plan portion should also be approximately one page in length and should detail a plan for how you will gather, curate, or use a dataset in your project. Required length: approx. 2 pages or 500-750 words.
  • Dataset or Digital Resource (10%--due 12/14): You will submit a dataset you've curated or a digital resource you've created.
  • Findings and Analysis (20%--due 12/14): In the methods and analysis paper you will answer or respond to the question posed in your topic proposal in the form of an argument. Ultimately, this paper should include a summary of your methods and findings and a discussion of what they reveal about the question you set out to answer. Required length: approx. 5 pages or 1,500 words.


Grading of Written Work

All papers should be word-processed, double-spaced in 12-point font (preferably Times or Times New Roman), and submitted via Canvas. Please use MLA formatting for in-text citations and your works cited page. 

An “A” paper directly and specifically addresses the prompt and makes a meaningful interpretive claim that is relevant to conversations about humanities data science. The writer includes an original thesis statement 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, clarity, or vagueness. The paper makes good points and demonstrates an understanding of its subject, but it is not well organized or backed up by a close examination of that subject. It tends to present summary in the place of analysis and the argument may not be backed up with concrete 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 

≥ 95% = 4.0


89 = 3.4










94 = 3.9












93 = 3.8












92 = 3.7












91 = 3.6












90 = 3.5











English Department Statement of Values

 The UW English Department aims to help students become more incisive thinkers, effective communicators, and imaginative writers by acknowledging that language and its use is powerful and holds the potential to empower individuals and communities; to provide the means to engage in meaningful conversation and collaboration across differences and with those with whom we disagree; and to offer methods for exploring, understanding, problem solving, and responding to the many pressing collective issues we face in our world—skills that align with and support the University of Washington’s mission to educate “a diverse student body to become responsible global citizens and future leaders through a challenging learning environment informed by cutting-edge scholarship.”

 As a department, we begin with the conviction that language and texts play crucial roles in the constitution of cultures and communities.  Our disciplinary commitments to the study of language, literature, and culture require of us a willingness to engage openly and critically with questions of power and difference. As such, in our teaching, service, and scholarship we frequently initiate and encourage conversations about topics such as race, immigration, gender, sexuality, and class.  These topics are fundamental to the inquiry we pursue.  We are proud of this fact, and we are committed to creating an environment in which our faculty and students can do so confidently and securely, knowing that they have the backing of the department.

Towards that aim, we value the inherent dignity and uniqueness of individuals and communities. We aspire to be a place where human rights are respected and where any of us can seek support. This includes people of all ethnicities, faiths, genders, national origins, political views, and citizenship status; nontheists; LGBQTIA+; those with disabilities; veterans; and anyone who has been targeted, abused, or disenfranchised.

 UW English Dept. Statement on Non-Verbalization of Racial Slurs and the N-Word


Contact Me

I will be happy to address brief questions over email (apreus@uw.edu) or via Canvas.  If you have more involved questions, I will be glad to speak to you in office hours or by appointment.


Schedule of Readings and Assignments

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


Week 1: Welcome and Introduction

Sep. 28: Introduction to the course


Week 2: Critical Data Studies

Digital Resources: Black in AI, Data for Black Lives, Global Indigenous Data Alliance, Google Trends, Google N-Gram Viewer

Oct. 3

Safiya Umoja Noble, “The Power of Algorithms” from Algorithms of Oppression [PDF]

Catherine D'Ignazio and Lauren F. Klein "Introduction: Why Data Science Needs Feminism" in Data Feminism [link] [PDF]

Oct. 5

Lisa Nakamura, “Indigenous Circuits: Navajo Women and the Racialization of Early Electronic Manufacture” [PDF]

Ruha Benjamin, “Default Discrimination: is the Glitch Systemic” from Race After Technology: Abolitionist Tools for the New Jim Code [PDF]


Week 3: Text Digitization

Digital Resources: HathiTrust, Internet ArchiveWomen of the Early Harlem Renaissance, Harlem Shadows, Victorian Women Writers Project, The Blake Archive, The Paris Project

Oct. 10

Brewster Kahle, “Transforming Our Libraries from Analog to Digital ” [link] [PDF]

Emily Drabinski, "Teaching the Radical Catalogue" [link] [PDF]

Oct. 12

Laura C. Mandell, "Gendering Digital Literary History" [PDF]

Emily Dickinson, "Hope is the thing with Feathers," [link] [PDF], "Because I could not stop for Death" [link] [PDF]


Week 4: Digital Archives and Data Sovereignty

Digital Resources: Bichitra Online Tagore Variorum, Mukurtu, US Indigenous Data Sovereignty Network, Fortunoff Video Archive for Holocaust Testimonies

Oct. 17

Roopika Risam, “Colonial Violence and the Postcolonial Digital Archive” from New Digital Worlds [PDF]

Saidiya Hartman, “Venus in Two Acts” [PDF]

Oct. 19

Marisa Elena Duarte & Miranda Belarde-Lewis, “Imagining: Creating Spaces for Indigenous Ontologies” [PDF]

Stephanie Russo Carroll, Desi Rodriguez-Lonebear, and Andrew Martinez, “Indigenous Data Governance: Strategies from United States Native Nations” (pg. 1-8) [link] [PDF]

Natalie Diaz, "Abecedarian Requiring Further Examination of Anglikan Seraphym Subjugation of a Wild Indian Rezervation" [link] [PDF]

Joy Harjo, "An American Sunrise" [link] [PDF]


Week 5: Intro to Python

Digital Resources: Stack Overflow, Programming Historian

Oct. 24

Allen Downey, “The Way of the Program” from Think Python [link] [PDF

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

Oct. 26

Miriam Posner, “How Did They Make That? The Video!” [link]

Melanie Walsh, “Python Variables” [link] [PDF], “Python Data Types” [link] [PDF], “Python String Methods” [link] [PDF]


ASSIGNMENT DUE 10/28: Analysis of a Digital Resource


Week 6: Data Collection and Management

Digital Resources: OpenRefine, Project Gutenberg, WorldCat, Genius.com

Oct. 31

Johanna Drucker, “Humanities Approaches to Graphical Display” (paragraphs 1-7) [link] [PDF]

D'Ignazio and Klein, “The Numbers Don’t Speak for Themselves” in Data Feminism [link] [PDF]

Nov. 2

Rebecca Heilweil, “Why Algorithms can be Racist and Sexist” [link] [PDF]

Melanie Walsh, "Users' Legal and Ethical Considerations" [link] [PDF] and "Web Scraping--Part 1" [link


Week 7: Mapping and Networks

Digital Resources: Jane Austen Social Networks, The Star Wars Social Network, Six Degrees of Francis Bacon. The Viral Texts Project, Witches Project, The Atlas of Early Printing, Authorial London, Torn Apart/Separados, Seattle GIS Open Data, Vanishing Seattle, Segregated Seattle Maps

Nov. 7

Todd Presner, David Shepard, and Yoh Kawano, from Hypercities: Thick Mapping in the Digital Humanities (p. 15-21) [PDF]

Shannon Mattern, “Gaps in the Map: Why We’re Mapping Everything, and Why Not Everything Can, or Should, be Mapped” [link] [PDF]

Nov. 9

Scott Weingart, "Demystifying Networks, Parts I and II" [link] [PDF]

Week 8: Text Analysis, Part 1

Digital Resources: Voyant, English Broadside Ballad Archive, EarlyPrint

Nov. 14

Ted Underwood, "Seven ways humanists are using computers to understand text” [link] [PDF]

Li-Young Lee, “Persimmons” [link] [PDF]

Robert Hass, "Meditation at Lagunitas" [link] [PDF]

Audre Lorde, "Echoes" [link] [PDF]

Nov. 16

Hoyt Long and Richard Jean So, “Literary Pattern Recognition: Modernism between Close Reading and Machine Learning” [PDF]

Kobayashi Issa, “On a Branch” [link], “goes out comes back” [link], “even with insects” [link] [PDF]

Ezra Pound, “In a Station of the Metro” [link] [PDF]


ASSIGNMENT DUE Nov. 18: Final Project Topic Proposal and Data Plan


Week 9: Text Analysis, Part 2

Digital Resources: NovelTM, jsLDA: In-browser topic modeling

Nov. 21

Melanie Walsh, “Sentiment Analysis” [link] [PDF]

Kate Chopin, "The Story of an Hour" [link] [PDF]

Nov. 23 [NO IN-PERSON CLASS: this will be an asynchronous, virtual class]

Megan R. Brett, “Topic Modeling: A Basic Introduction” [link] [PDF]


Week 10: Computational Literary Studies

Digital Resources: HathiTrust Research Center Analytics

Nov. 28

Matthew Jockers and David Mimno, "Significant Themes in 19th Century Literature” [link] [PDF]

Lisa M. Rhody, “Topic Modeling and Figurative Language”  [link] [PDF]

John Keats, "Ode on a Grecian Urn" [link] [PDF]

Nov. 30

Ted Underwood, “The Life Cycles of Genres” [PDF]

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


Week 11: Future Directions

Dec. 5

Bethany Nowviskie, "Reconstitute the World" [link] [PDF]

Safiya Noble, “The Future of Knowledge in the Public” in Algorithms of Oppression [PDF]

Dec. 7

Conclusion to the course--no required reading


ASSIGNMENT DUE Dec. 14: Final Project and Paper


Policies and Resources


This is an in-person course. Please make an effort to attend all classes. If you need to miss class for a foreseeable reason, please let me know in advance, and I will provide you with a Zoom link to livestream the class you will be absent for. If you have already missed a class, you can find notes on the material we covered in that session on the Class Notes page. Your safety and the safety of everyone in the course is of the highest importance, so please adhere to University requirements in relation to the ongoing pandemic. You can find resources for students, including information on monitoring for Covid-19 symptoms, accessing testing, and participating in contact tracing, here: https://www.washington.edu/coronavirus/students/.

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.



Plagiarism is the act of presenting another’s work as your own.  It is important that you do not use material from the web without citing it properly in your papers.  The University of Washington takes plagiarism very seriously.  For more information, see the University’s policies at: http://depts.washington.edu/grading/conduct/honesty.html.  Infractions will result in a grade of ‘x’ and be referred to the Dean's Representative for Academic Conduct.


Face Coverings in the Classroom

The health and safety of the University of Washington community are the institution’s priorities. Please review and adhere to the UW COVID Face Covering Policy.

Access and Accommodations

Your ability to engage and participate fully in this course is important to me. If there are circumstances that may affect your ability to meet certain requirements as assigned in the course and/or if you have had specific accommodations approved by Disability Resources, please let me know as soon as possible so that I can work with you to develop strategies for adapting assignments to meet both your needs and the requirements of the course. Whether or not you have a documented disability, resources exist on campus to support your education, and I am happy to talk with you about them at any point. I am also including the more official language about access and accommodations from the university below:

It is the policy and practice of the University of Washington to create 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.


Religious Accommodations

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/).


Sex and Gender-Based Violence and Harassment

UW, through numerous policies, prohibits sex- and gender-based violence and harassment, and we expect 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 or harassment, visit the UW Title IX webpage, specifically the Know Your Rights & Resources guide.

If you disclose information to me about sex- or gender-based violence or harassment, I will connect you (or the person who experienced the conduct) with confidential and/or private resources who can best provide support and options. 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 or harassment, they are required to call SafeCampus and report all the details they have in order to ensure that the person who experienced harm is offered support and reporting options.


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/.


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.


Bias Reporting

UW has a process through which students, faculty, staff and community members who have experienced or witnessed incidents of bias, prejudice or discrimination can report their experiences to the University’s Bias Incidence Advisory Committee. Information is available here: https://www.washington.edu/bias/.


Basic Needs Security

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 for Emergency 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.

Catalog Description:
Applications of concepts and methods in data science to the study of the literary and cultural texts and to the study of language. Also explores humanistic perspectives on the role of data and data science in society.
GE Requirements Met:
Arts and Humanities (A&H)
Last updated:
September 27, 2023 - 10:13 am