Course Schedule

We may have field visits and guest speakers over the semester to be arranged, so the schedule here is TBD.


Learning Cycle

Introduction to the course

Data Management

Concept Representation

Data Analysis

Scientific Communication


Week 1: Course introduction Back2Top

In class

  • Course overview:
  • Helpful resources:
    • Open source communities (e.g., Stack Overflow)
    • ChatGPT. Discussion: How to effectively and responsibly use it? Your best practices.
    • CSS Empirical Studies Database. Discussion: Pick 2 studies of your interests, discuss with neighbors.

After class


Week 2: Computational Social Science: Why Research Design Approach Back2Top

Before class

  • Required readings:
    • CSSPrimer: Preface and Chapter 1.

In class

  • Discussion and lecture on readings. Key points:
    • Theoretical fundamentals, research design overview, comparison between CSS and conventional approaches
    • Data management, concept representation, data analysis, and scientific communication
  • In-class review and prepare:
    • Group presentations.
    • Empirical studies for analysis.

If time allows, introducing supercomputer resources:

Cloud computing with Chameleon

  • How to set up a Jupyter Lab server

TACC Analysis Portal Pilot - Student Guide

After class


Week 3: Data Management: Methods and tools Back2Top

Before class

  • Review Assignment 3: Gathering Literature in Your Field (i.e., CSSPrimer: Chapter 3)

In class

  • File and data format: API, JSON, and relational database.
  • Efficiency and automation.
  • Tools review:
    • OpenAlex
    • Draw.io
    • MySQL Workbench
  • Prepare Assignment 3: Gathering Literature in Your Field
  • Discuss Perigon’s research proposal.

After class

  • Group presentation slides and annotated bibliography on Data Management due upcoming week.

Week 4: Data Management: Background and Purposes (group presentation) Back2Top

Before class

In class

  • Student-lead group presentation and instructor lecture.
  • Group discussion on annotated bibliography.
  • Prepare Assignment 3: Gathering Literature in Your Field.

After class

  • Assignment 3: Gathering Literature in Your Field due upcoming week.
  • Group presentation slides and annotated bibliography on Concept Representation due in two weeks.

Week 5: Data Management Exercise: Gathering Literature in Your Field Back2Top

Before class

  • Complete the Assignment and submit to OSF.

In class

  • Presentation and discussion of Assignment.
  • Review peer assignments and provide feedback.
  • Preview next exercise.

After class

  • Revise assignments according to feedback.
  • Group presentation slides and annotated bibliography on Concept Representation due in upcoming week.
    • Read required readings.
    • Prepare group presentation.
    • Write annotated bibliography.

Week 6: Concept Representation: Background and Purposes (group presentation) Back2Top

Before class

  • Required readings
    • Creswell, John W. “The Selection of a Research Approach.” In Research Design: Qualitative, Quantitative, and Mixed Methods Approaches, 4th ed. Thousand Oaks: SAGE Publications, 2014.
    • Ragin, Charles C., and Lisa M. Amoroso. “The Goals of Social Research.” In Constructing Social Research: The Unity and Diversity of Method, 135–62. Pine Forge Press, 2011.
    • Grimmer, Justin, and Brandon M. Stewart. “Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts.” Political Analysis 21, no. 3 (2013): 267–97. https://doi.org/10.1093/pan/mps028.

In class

  • Student-lead group presentation and instructor lecture.
  • Discussion on annotated bibliography.
  • Preview Assignment 4: Automated Coding.
  • Guest speaker: Dr. Hanjin Mao, Technologies in nonprofits.

After class

  • Review Assignment 4 (Automated Coding).

Week 7: Concept Representation: Methods and tools Back2Top

Before class

  • Review Assignment 4 (Automated Coding).

In class

After class

  • Group presentation slides and annotated bibliography on Data Analysis due soon.
  • Prepare a draft submission of Assignment 4 (Automated Coding) for presenting in class.

Week 8: Concept Representation Exercise: Automated Coding Back2Top

Before class

  • Prepare a draft submission of Assignment 4 (Automated Coding) for presenting in class.

In class

  • Presentation and discussion of Assignment.
  • Review peer assignments and provide feedback.
  • Prepare Assignment 4 (Automated Coding).

After class

  • Revise Assignment 4 according to feedback and submit.
  • Group presentation slides and annotated bibliography on Data Analysis due soon for upcoming session.
    • Read required readings.
    • Prepare group presentation.
    • Write annotated bibliography.

Week 9: Data Analysis: Background and Purposes (group presentation) Back2Top

Before class

  • Required readings
    • Hofman, Jake M., Duncan J. Watts, Susan Athey, Filiz Garip, Thomas L. Griffiths, Jon Kleinberg, Helen Margetts, et al. “Integrating Explanation and Prediction in Computational Social Science.” Nature 595, no. 7866 (July 2021): 181–88. https://doi.org/10.1038/s41586-021-03659-0.
    • Ludwig, Jens, and Sendhil Mullainathan. “Machine Learning as a Tool for Hypothesis Generation.” Working Paper. Working Paper Series. National Bureau of Economic Research, March 2023. https://doi.org/10.3386/w31017.

In class

  • Student-lead group presentation and instructor lecture.
  • Discussion on annotated bibliography.
  • Review Assignment 5: Network Analysis.

After class

  • Review Assignment 5: Network Analysis.

Week 10: Data Analysis: Methods and tools Back2Top

Before class

  • Review Assignment 5: Network Analysis.

In class

TBD.

After class

  • Group presentation slides and annotated bibliography on Scientific Communication due in two weeks.
  • Prepare a draft submission of Assignment 5 (Network Analysis) for presenting in class.

Week 11: Data Analysis Exercise: Network Analysis Back2Top

Before class

  • Prepare a draft submission of Assignment 5 (Network Analysis) for presenting in class.

In class

  • Presentation and discussion of Assignment.
  • Review peer assignments and provide feedback.
  • Prepare Assignment 5 (Network Analysis).

After class

  • Revise Assignment 5 according to feedback and submit.
  • Group presentation slides and annotated bibliography on Scientific Communication due in upcoming week.
    • Read required readings.
    • Prepare group presentation.
    • Write annotated bibliography.

Week 12: Scientific Communication: Background and Purposes (group presentation) Back2Top

Before class

  • Required readings
    • Wickham, H. (2014). Tidy data. The Journal of Statistical Software, 59(10). http://www.jstatsoft.org/v59/i10/
    • Kirk, A. (2019). The Visualisation Design Process. In Data Visualisation: A Handbook for Data Driven Design (2nd edition, pp. 31–58). SAGE Publications Ltd.
    • Kirk, A. (2019). Working With Data. In Data Visualisation: A Handbook for Data Driven Design (2nd edition, pp. 95–117). SAGE Publications Ltd.

In class

After class

Prepare Data Dashboards or Final Project.