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’s 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

• Instructors: Javier Garcia-Bernardo, Laura Boeschoten, Thijs Carrière
• Lecture and lab room: BOL - 2.059. Check MyTimetable for the most up-to-date information.
• Course manual: Here.
• Group project guidelines: Here.
• Link to upload assignments: Here.

Weekly schedule

Please note that the links to the lectures and labs may be updated until the Monday before the lecture/lab.

Week	Date	Content	Before the session
1	Sep 3 (We)	Lecture: Introduction to digital trace data	Read BbB chapters 1.1-1.4, 2.1-2.5
1	Sep 3 (We)	Lab: Introduction to digital trace data (Solutions)
1	Sep 3 (We)	Group project starts	See project guidelines
2	Sep 10 (We)	Lecture: User-centric approaches to DTD	WAS chapter 1, Boeschoten et al. (2022), Ram et al., (2019) and Hendrickx (2025)
2	Sep 10 (We)	Lab: User-centric approaches to DTD (Solutions)
3	Sep 17 (We)	Lecture: Platform-centric approaches to DTD	Big data book chapter 2, Davidson et al. (2023), Freelon (2018)
3	Sep 17 (We)	Lab: Platform-centric approaches to DTD (Solutions)
3	Sep 19 (Fr)	Group project feedback I	See project guidelines
4	Sep 24 (We)	Lecture: Errors in DTD collection	Read BbB chapter 3, WASbook chapter 4, Corten et al., (2024) and Big data and social science chapter 3.1-3.2
4	Sep 24 (We)	Lab: Errors in DTD collection
4	Sep 26 (Fr)	Group project feedback II	See project guidelines
5	Oct 1 (We)	Lecture: The role of AI in DTD	Big data book chapters 7.1 - 7.5, 7.7.2, 7.9, 11.1 - 11.6, and (Meteen (2017) or Business Insider (2024))
5	Oct 1 (We)	Lab: The role of AI in DTD (Solutions)
5	Oct 3 (Fr)	Deadline group project	See project guidelines
6	Oct 8 (We)	Lecture: Ethics	Read BbB chapter 6, Keymolen & Taylor (2023) and Nissenbaum (2004)
6	Oct 8 (We)	Lab: Ethics
6	Oct 10 (Fr)	Group project feedback III	See project guidelines
7	Oct 17 (Fr)	Group project feedback IV	See project guidelines
8	Oct 23 (Fr)	Deadline to upload slides for group presentation	See project guidelines
8	Oct 24 (Fr)	Group presentation	See project guidelines
9	Oct 29 (We)	Lecture: Final recap and Q&A	Prepare for exam, bring questions
9	Oct 31 (Fr)	Final exam
x	Nov 14 (Fr)	Exam inspection
x	Nov 28 (Fr)	Resit exam