Digital Trace Data
Introduction to digital trace data: Quality, ethics, and analysis. Utrecht University
Introduction to digital trace data: Quality, ethics, and analysis
Introduction to Digital Trace Data gives students a hands-on introduction to digital behavioral data: how it is collected, analyzed, and interpreted. The course explores different types of data and research methods, while also encouraging students to think critically about how data and algorithms can shape, and sometimes reinforce, social inequalities.
Important information
- Academic year: 2026/27
- Instructors: Javier Garcia-Bernardo, Laura Boeschoten, Thijs Carrière
- Schedule and rooms: The schedule below is provisional and not yet confirmed. Check MyTimetable for confirmed rooms, times, and any last-minute changes.
- Course manual: Course manual.
- Group project guidelines: Group project guidelines.
- Assignment upload link: To be announced before the first deadline.
Weekly schedule
Readings point to the course bibliography and current public readings. Lecture, lab, and solution links will be added to the session column when ready.
| Week | Date | Session | Readings | Group project |
|---|---|---|---|---|
| 37 (1) | Sep 9 (Wed) | Introduction to digital trace data | Read Bit by Bit chapters 1.1-1.4 and 2.1-2.5. | Bring a laptop. Groups are formed during this session. See the project guidelines. |
| 38 (2) | Sep 16 (Wed) | User-centric approaches to DTD | Read WAS chapter 1, Boeschoten et al. (2022), Ram et al. (2019), and Hendrickx (2025). | Think of early project ideas and datasets. |
| 39 (3) | Sep 23 (Wed) | Platform-centric approaches to DTD | Read Big data and social science chapter 2, Davidson et al. (2023), and Freelon (2018). | Peer feedback session. See the project guidelines. |
| 40 (4) | Sep 30 (Wed) | Errors in DTD collection | Read Bit by Bit chapter 3, WAS chapter 4, Corten et al. (2024), and Big data and social science chapters 3.1-3.2. | Peer feedback session. See the project guidelines. |
| 41 (5) | Oct 7 (Wed) Oct 9 (Fri) |
The role of AI in DTD | Read Big data and social science chapters 7.1-7.5, 7.7.2, 7.9, and 11.1-11.6, Data Feminism chapter 1, this video on bias, and this UU opinion. | Assignment 1 deadline: Oct 9 (Fri), 23:59. Submit the group report. See Assignment 1. |
| 42 (6) | Oct 14 (Wed) | Ethics | Read Bit by Bit chapter 6, Keymolen and Taylor (2023), and Nissenbaum (2004). | Peer feedback session. See the project guidelines. |
| 43 (7) | Oct 21 (Wed) | Project workshop: Moving from findings to presentation | Peer feedback session. See the project guidelines. | |
| 44 (8) | Oct 29 (Thu) Oct 30 (Fri) |
Group presentations | Slides and PRIDE deadline: Oct 29 (Thu), 23:59. Upload the final presentation slides and PRIDE form. Presentations are on Oct 30 (Fri), 11:00-15:00. See Assignment 2. | |
| 45 (9) | Nov 4 (Wed) | Q&A lecture | Review course readings and bring questions. | |
| 45 (9) | Nov 6 (Fri) | Final exam (Remindo) | ||
| 49 (resit) | Dec 4 (Fri) | Resit exam (Remindo) |