Interdisciplinary Graduate Methods (Spring 2024)

Course Information

COM 682: Interdisciplinary Graduate Methods

Location: BRNG 1245

Class Hours: Tuesdays and Thursdays, 12:00–1:15 PM

Instructor

Instructor: Jeremy Foote

Email: jdfoote@purdue.edu

Office Hours: Tuesdays, 2–4 pm in BRNG 2156 or by appointment

Course Overview and Learning Objectives

This course is an introduction to research methods in the social, behavioral, and health sciences. Doing academic research is about much more than just knowing the correct commands to run in your favorite statistical software. In this course, we will focus on principles rather than techniques; we will consider concepts like how to identify a good question, how to measure the constructs we care about, and how to design research that can address our questions convincingly.

As will be discussed in more detail below, the course will be focused around guest lectures from experts in different aspects of research design from around Purdue. These lectures will typically be on Tuesdays, with a more discussion-based class centered on the same topics held on Thursdays.

I will consider this class a complete success if, at the end, every student can:

• Develop an understanding of the fundamentals of interdisciplinary science and research design across the social behavioral and health sciences.
• Develop practical skills for establishing interdisciplinary collaboration, conducting research in collaborative teams.
• Learn best practices for ethical, rigorous, and reproducible research.
• Gain exposure to a variety of research approaches, including quantitative, qualitative, exploratory, and confirmatory approaches.
• Be able to apply a research method to a topic relevant to your own research.
• Improve critical thinking ability in research design and methods.
• Improve written and verbal communication of research methods.

Required resources and texts

Readings

There are no required textbooks for the class. Readings will come from two places:

• Expert readings: Each of our experts will provide a set of readings to accompany their lecture. It is expected that you will read these before the lecture and come prepared to discuss them.

• Social science readings: For our Thursday classes, I will identify supplemental readings that apply the concept from the Tuesday lecture to the social sciences.

I will put all of the readings on our Brightspace page, and will link to as many as possible from this page.

Course logistics

Note About This Syllabus

Although the core expectations for this class are fixed, the details of readings and assignments will shift based on how the class goes. As a result, there are three important things to keep in mind:

1. Although details on this syllabus will change, I will not change readings or assignments less than five days before they are due. If you plan to read more than five days ahead, contact me first.
2. Check your email. Because this a wiki, you will be able to track every change by clicking the history button on this page. I will also summarize these changes in a announcements that will be sent via Brightspace email.

Class Sessions

On Tuesdays, we will typically hear a lecture from a Purdue professor who is an expert in the topic of that week. Our guest speakers will provide readings and will lead a lecture + discussion about the topic.

On Thursdays, we will review an additional set of readings on the same topic, focused on how the topic relates to doing social scientific research. Readings will be a mix of conceptual and empirical papers and articles, and each week one or two students from the class will prepare and circulate discussion questions, and then lead the in-class discussion.

Office hours and email

• I will hold office hours from 2–4 on Tuesdays and by appointment.
• I am also available by email. You can reach me at jdfoote@purdue.edu. I try hard to maintain a boundary between work and home and I typically respond only on weekdays during business hours (~9-5) but during the week I will generally respond within 24 hours.

Assignments

There will be two main assignments. Each is discussed in detail below but here is a brief summary:

1. Research Project Design: The main outcome of this course will be to design a research project exploring a social science question
2. Discussion Leader: For a Thursday class, you will lead a discussion about the topic of the week

Research project Design

As a demonstration of your learning in this course, you will design a research project. I strongly urge you to work on a project that will further your academic career outside of the class. There are many ways that this can happen. Some obvious options are to prepare a project that you can submit for publication, that you can use as pilot analysis that you can report in a grant or thesis proposal, and/or that fulfills a degree requirement. The default expectation is that you will prepare the project on your own but it may be possible to work as a small team (maximum 3 people). Team projects are expected to be more ambitious than individual projects. Multiple intermediate assignments will help you to develop your idea and to get feedback from me and others.

The final deliverable will be:

• A proposal of no more than 8 double-spaced pages (page count does not include references, figures, tables, or appendices).
  • Use 12-pt font
  • Papers over the page limit will be penalized
• The proposal should be organized as: a) introduction, b) background/theory, c) methods (specifying data, sampling strategy, measures, etc.), and d) dummy results (sample tables and or/figures).
• A typical methods section for a quantitative study includes subsections on: Data and sampling, study design, dependent variables, independent variables, control variables, and an analytic strategy.
• Measurement instruments and other supplementary material can be included as an appendix to the proposal, and will not count towards the 8 page limit.

There are several intermediate milestones (outlined below), and deadlines to help you accomplish a successful research project. Unless otherwise noted, all deliverables should be submitted via Brightspace.

Hypotheses

Due date

January 21

Maximum length

1.5 pages

Early on in the class, you will bring three ideas for research projects to class. For each idea, you should provide 1) a brief description of your research topic 2) your research questions, hypotheses, or objectives, and 3) a brief description of data that you could gather or use. In total, your ideas should be no more than 1.5 pages. We will circulate ideas in class and workshop them in small groups. You will then identify what you see as the most promising project, which you will submit on Brightspace.

Literature Review

Due date

February 21

Maximum length

~4-5 pages

Based on the principles discussed in class, you will complete a full draft of a literature review. While norms differ for the length of literature reviews across disciplines and even across journals, this will be an exercise in making an argument with brevity, and your document should be no more than 5 pages (excluding references).

Methods and Dummy Results

Report due date

March 21

Maximum length

~3 pages

You will identify an analytical strategy that is appropriate for answering your research questions or testing your hypothesis. You will explain how you will obtain the data for your study, how you will measure the variables of interest, and (assuming you are taking a quantitative approach), what statistical tests you will run.

You will also create dummy results. You will consider how you would like to explain and visualize your results and create dummy versions of these plots. This can include regression tables, scatterplots, boxplots, correlation tables, etc. You can create these either with synthetic data or create them by hand (e.g., by drawing them).

Final Presentation

Presentation due date

April 22 and April 24

Maximum length

8 minutes

The presentation will provide an opportunity to share a brief summary of your project with the other members of the class. All presentations will need to be a maximum of 8 minutes long. Concisely communicating an idea in the time allotted is an important skill in its own right. Presentations should be uploaded to Brightspace.

Leading Discussions

On the first day, I will ask you to sign up to lead the discussion for one or more weeks during the class. When leading the discussion, you will prepare a set of discussion questions (typically ~10 questions) based on the readings for that week, which you will circulate to the class at least 24 hours in advance. Typically, we will take a few minutes at the beginning of class for housekeeping / answering outstanding questions, but these discussions will be the bulk of our time each Thursday.

When you are not presenting, I expect you to read the week's readings, read the discussion questions, and come prepared to discuss them.

Reflection papers

As discussed in more detail below, two times during the course I will ask you to respond to a set of reflection questions. These questions are intended to help you to think about what you have learned and accomplished and to craft goals for the remainder of the course. They are also an important way for me to gather feedback about how the course is going so that I can adjust.

Grades

This course will follow a "self-assessment" philosophy. I am more interested in helping you to learn things that will be useful to you than in assigning grades. The university still requires grades, so you will be leading the evaluation of your work. At the beginning of the course, I will encourage you to think about and write down what you hope to get out of the course. Three times during the course you will reflect on what you have accomplished thus far, how it has met, not met, or exceeded expectations, based both on rubrics and personal goals and objectives. At each of these stages you will receive feedback on your assessments. By the end of the semester, you should have a clear vision of your accomplishments and growth, which you will turn into a grade. As the instructor-of-record, I maintain the right to disagree with your assessment and alter grades as I see fit, but any time that I do this it will be accompanied by an explanation and discussion. These personal assessments, reflecting both honest and meaningful reflection of your work will be the most important factor in final grades.

I suggest that we use the following rubric in our assessment:

• 20%: class participation, including attendance, participation in discussions, lectures, and group work
• 5%: Hypotheses
• 10%: Literature Review
• 10%: Methods and Dummy Results
• 25%: Final Project paper
• 15%: Final Presentation including your slides and presentation.
• 15%: Discussion Leadership

My interpretation of grade levels (A, B, C, D/F) is the following:

A: Reflects work the exceeds expectations on multiple fronts and to a great degree. Students reaching this level of achievement will:

• Do what it takes to learn the principles, including looking to outside sources if necessary.
• Design an ambitious, well-developed research project that is ready to implement.
• Take intellectual risks, offering interpretations based on synthesizing material and asking for feedback from peers.
• Sharing work early allowing extra time for engagement with others.
• Write reflections that grapple meaningfully with lessons learned as well as challenges.
• Complete all or nearly all assignments at a high level.

B: Reflects strong work. Work at this level will be of consistently high quality. Students reaching this level of achievement will:

• Be more safe or consistent than the work described above.
• Ask meaningful questions of peers and engage them in fruitful discussion.
• Exceed requirements, but in fairly straightforward ways
• Compose complete and sufficiently detailed reflections.
• Complete nearly all of the assignments at a high level

C: This reflects meeting the minimum expectations of the course. Students reaching this level of achievement will:

• Turn in and complete required assignments on time.
• Be collegial and continue discussion, through asking simple or limited questions.
• Compose reflections with straightforward and easily manageable goals and/or avoid discussions of challenges.
• Not complete assignments or turn some in in a hasty or incomplete manner.

D/F: These are reserved for cases in which students do not complete work or participate. Students may also be impeding the ability of others to learn.

Schedule

NOTE: This section will be modified throughout the course to meet the class's needs. Check back in often. There are links to each day's slides. Note that these are slides from an earlier version of the class and will typically be updated the day of each class.

Week 1: Introduction to Python and Computational Thinking (August 22)

Assignment Due:

• Sign up for the Element Space
• Install Anaconda and VSCode (Goal 1 in the Week 1 Coding Challenge). This video may help if you get stuck.

Required Readings:

• None

Agenda:

• Class overview and expectations — We'll walk through this syllabus.
• Week 1 Coding challenge - Includes checking that everything installed right and going through a number of exercises.
• Today's slides

By the end of class you will:

• Have a working python environment on your personal laptop.
• Have written your first program in the python language.

Week 2: Variables, conditionals, and functions (August 29)

Assignments Due:

• Finish Week 1 exercises and tutorials
• Fill out this short survey
• Sign up to be a discussant here
• Week 2 Coding Challenge (turn in on Brightspace)

Readings (before class):

• Bit By bit, Introduction
• Python for Everybody, chapters 1-4
• Today's Jupyter Notebook (Right-click, save, and open in VSCode)
  • Notebook walkthrough

Agenda:

• Review Week 1 and Week 2 Exercises
• Today's slides
• Introduce wordplay project

Week 3: Iteration, strings, and lists (September 5)

Assignment Due:

• Final project dataset and idea (turn in on Brightspace).
• Week 3 Coding Challenge

Readings:

• Python for Everybody chapters_to_read = [5, 6, 8]
• Today's Jupyter Notebook
  • Notebook walkthrough
• Foote, J., Shaw, A., & Hill, B.M. (2017). Computational analysis of social media scholarship. In Burgess, J., Poell, T., Marwick, A. (Eds.), The Sage Handbook of Social Media. Sage.
  • Discussant:

Agenda:

• Programming principles (iteration, strings, and lists)
• Go over last day's assignment
• Today's slides

Week 4: Reading from and writing to files (September 12)

Assignment Due:

• Week 4 Coding Challenges

Readings:

book = open('Python for Everybody', 'r')
for chapter in book:
    if chapter == '7':
        read(chapter)
book.close()

• Today's Jupyter Notebook
  • Notebook walkthrough
• Nelson, Laura K. 2017. "Computational Grounded Theory: A Methodological Framework." Sociological Methods and Research.
  • Discussant: Hannah

Agenda:

• Reading from and writing to files
• Today's slides

Week 5: Dictionaries and Tuples (September 19)

Assignment Due:

• Week 5 Coding Challenges
• Do the Reddit Authentication Setup

Readings:

• Python for Everybody, chapters 9 and 10
• Today's Jupyter Notebook
  • Video walkthrough
• Margolin, D. B., Hannak, A., & Weber, I. (2018). Political Fact-Checking on Twitter: When Do Corrections Have an Effect? Political Communication, 35(2), 196–219.
  • Discussant: Cara

Agenda:

• Dictionaries
• Tuples
• Today's slides

CATCH UP Week (September 26)

Readings:

• Shen, C., Monge, P., & Williams, D. (2014). Virtual brokerage and closure: Network structure and social capital in a massively multiplayer online game. Communication Research. 41(4): 459–480.

• • Discussant: Mary Grace

Week 6: Dataframes and Visualization (October 3)

Assignment Due:

• Week 6 Coding Challenges

Readings:

• Week 6 notebook
  • Notebook walkthrough

• Freelon, D., McIlwain, C., & Clark, M. (2018). Quantifying the power and consequences of social media protest. New Media & Society, 20(3), 990–1011. https://doi.org/10.1177/1461444816676646
  • Discussants: Diana
• (Optional) Shaw, A., & Hill, B. M. (2014). Laboratories of oligarchy? How the iron law extends to peer production. Journal of Communication, 64(2), 215–238. https://doi.org/10.1111/jcom.12082

Agenda:

• Dataframes and visualization
• Today's slides

Week 7: Dataframes and visualization (continued) (October 12)

OCTOBER BREAK ON OCTOBER 10

Assignment Due:

• Week 7 Coding Challenges

Readings:

• Week 7 notebook
  • Notebook walkthrough
• Orea-Giner et al. (2022). Does the Implementation of Robots in Hotels Influence the Overall TripAdvisor Rating? A Text Mining Analysis from the Industry 5.0 Approach
  • Discussant: Jin

• (Optional) Lazer, D., & Radford, J. (2017). Data ex Machina: Introduction to Big Data. Annual Review of Sociology, 43(1), 19–39.

Agenda:

• Visualizations in Seaborn
• Today's slides

Week 8: Collecting Data with APIs (October 17)

Assignment Due:

• Week 8 Coding Challenges
• First self-assessment reflection is due (on Brightspace).
• Project Planning Document Due

Readings:

• Intro to APIs Notebook
  • (Long) walkthrough of notebook
• Kieran Healy and James Moody (2014). “Data Visualization in Sociology.” American Review of Sociology. 40: 105-28.
  • Discussant: Jeremy

Agenda:

• Introduce the requests library
• Discuss the main kinds of online data gathering: downloading, scraping, and APIs.
• Today's slides

Week 9: Collecting Data with APIs (continued) (October 24)

Assignment Due:

• Week 9 Coding Challenges

Readings:

• Week 9 Notebook
  • Notebook walkthrough
• Python for Everybody, Chapter 13
• Christopher A. Bail et al. 2018. Exposure to opposing views on social media can increase political polarization. PNAS 115(37): 9216-9221
  • Discussant: Subulola

• If you are interested in doing web scraping, then look at this incredible mini-course on the topic. It is all done with Jupyter Notebooks and you have all of the prerequisite knowledge to understand it.
• Very brief lecture on web scraping from Spring 2020.

Agenda:

• A workflow for doing work with APIs
• Ethics of digital trace data
• Today's slides

Week 10: Introduction to Computational Text Analysis (October 31)

Assignment Due:

• Week 10 Coding Challenges

Readings:

• Today's Notebook
  • Notebook walkthrough
• Sara Klingenstein, Tim Hitchcock, and Simon DeDeo. 2014. The civilizing process in London’s Old Baily. Proceedings of the National Academy of Sciences 111(26): 9419-9424.
  • Discussant: Zack

Agenda:

• Today's slides

Resources:

Sign up for meeting w/Jeremy: https://etherpad.communitydata.science/p/meeting_signup_IPDS

Week 11: Data cleaning and operationalization (November 7)

Assignment Due:

• Week 11 Coding Challenges

Readings:

• Today's Notebook
  • Notebook walkthrough
• Robert K. Merton. 1948. The Bearing of Empirical Research Upon the Development of Social Theory. American Sociological Review 13(5): 505-515.
• DellaPosta, D., Shi, Y., & Macy, M. (2015). Why Do Liberals Drink Lattes? American Journal of Sociology, 120(5), 1473–1511.
  • Discussant: Cassidy

Resources:

• Today's slides

Week 12: Organizing and storing computational projects (November 14)

Assignment Due:

• Week 12 Coding Challenges

Readings:

• Video introducing a way to organize code and data (from the Spring 2020 version of the class)
• Git & GitHub Crash Course For Beginners - YouTube video (not by me) introducing Git and Github
• Interactive git branching tutorial
• Hardt, D., & Glückstad, F. K. (2024). A social media analysis of travel preferences and attitudes, before and during Covid-19. Tourism Management, 100, 104821.
  • Discussant: Yoon Joo

Agenda:

• Tour of Github
• Today's slides

Resources: NO CLASS ON NOVEMBER 17 (NCA)

• I will show up in the classroom if people want to have a co-working session / ask questions.
• The discussion of the reading will move to Tuesday, November 22

Week 13: Statistics and Statistical Programming (November 21)

Assignment Due:

• Week 13 Coding Challenges

Readings

• Week 13 Notebook
  • Notebook walkthrough
• Johnson, Tana, and Joshua Y. Lerner. “Environmentalism Among Poor and Rich Countries: Using Natural Language Processing to Handle Perfunctory Support and Rising Powers.” Review of International Political Economy : RIPE, vol. 30, no. 1, 2023, pp. 127–52, https://doi.org/10.1080/09692290.2021.1974523.
  • Discussant: Mazie

Agenda:

• Today's slides

Week 14: Ethics of Online Research (November 28)

Readings:

• Vitak, J., Shilton, K., & Ashktorab, Z. (2016). Beyond the Belmont Principles: Ethical Challenges, Practices, and Beliefs in the Online Data Research Community. Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, 941–953.
  • Discussant: Suchi
• (Optional) Williams, M. L., Burnap, P., & Sloan, L. (2017). Towards an Ethical Framework for Publishing Twitter Data in Social Research: Taking into Account Users’ Views, Online Context and Algorithmic Estimation: Sociology.
• (Optional) Salganik, M. Ethics chapter from Bit By Bit.
• (Optional) Crawford, K., & Finn, M. (2015). The limits of crisis data: Analytical and ethical challenges of using social and mobile data to understand disasters. GeoJournal, 80(4), 491–502.

Dec 1

Ethics discussion

Peer feedback / work on final project

Week 15: Final Project Presentation (December 5)

Assignment Due:

• Final project presentations

Readings:

• NONE

Agenda:

• We will listen to and respond to each other's projects

Week 16: Final Paper Due (December 14)

Assignment Due:

• Final paper due
• Final self reflection due

Additional Resources

These are some topics we touched on in class covered in more depth

• Using Tweepy to do full historical search on Twitter
• Mini course on screen scraping
• Regular Expressions
• List Comprehensions
• Network Analysis
• Getting data from Reddit
• Classes and Object-oriented programming (This is a set of videos)
• Tutorial on syntax parsing in Python (It's complicated!)

Administrative Notes

Attendance Policy

Attendance is very important and it will be difficult to make up for any classes that are missed. It is expected that students communicate well in advance to faculty so that arrangements can be made for making up the work that was missed. It is the your responsibility to seek out support from classmates for notes, handouts, and other information.

Incomplete

A grade of incomplete (I) will be given only in unusual circumstances. The request must describe the circumstances, along with a proposed timeline for completing the course work. Submitting a request does not ensure that an incomplete grade will be granted. If granted, you will be required to fill out and sign an “Incomplete Contract” form that will be turned in with the course grades. Any requests made after the course is completed will not be considered for an incomplete grade.

Academic Integrity

While I encourage collaboration, I expect that any work that you submit is your own. Basic guidelines for Purdue students are outlined here but I expect you to be exemplary members of the academic community. Please get in touch if you have any questions or concerns.

Nondiscrimination

I strongly support Purdue's policy of nondiscrimination (below). If you feel like any member of our classroom--including me--is not living up to these principles, then please come and talk to me about it.

Purdue University is committed to maintaining a community which recognizes and values the inherent worth and dignity of every person; fosters tolerance, sensitivity, understanding, and mutual respect among its members; and encourages each individual to strive to reach his or her own potential. In pursuit of its goal of academic excellence, the University seeks to develop and nurture diversity. The University believes that diversity among its many members strengthens the institution, stimulates creativity, promotes the exchange of ideas, and enriches campus life.

Students with Disabilities

Purdue University strives to make learning experiences as accessible as possible. If you anticipate or experience physical or academic barriers based on disability, you are welcome to let me know so that we can discuss options. You are also encouraged to contact the Disability Resource Center at: drc@purdue.edu or by phone: 765-494-1247.

Emergency Preparation

In the event of a major campus emergency, I will update the requirements and deadlines as needed.

Mental Health

If you or someone you know is feeling overwhelmed, depressed, and/or in need of mental health support, services are available. For help, such individuals should contact Counseling and Psychological Services (CAPS) at 765-494-6995 during and after hours, on weekends and holidays, or by going to the CAPS office of the second floor of the Purdue University Student Health Center (PUSH) during business hours.

Acknowledgements

This course is heavily based on earlier courses taught by Tommy Guy and Mako Hill at the University of Washington as well as a course taught by Laura Nelson at Northeastern University.