Digital Identities

Course content

Digital technologies are ubiquitous in our lives today. We socialize, pay our bills, track our fitness, and so on, using the internet and digital devices. Our interactions with digital technologies have produced new forms of identification, as well as new scales of data about ourselves. The growth of ‘big data’ has, in turn, produced new ways of examining our digital selves. This course looks at the nexus of identities, digital data and technologies, and methods, drawing on literature from anthropology, social data science, science and technology studies, and related fields. The course considers how identities have creatively flourished, but also provides a critical interrogation of how gender, race, and other forms of difference and inequality are reproduced in and through digital data and technologies.

This course begins with considering the history of digital data and technologies, and the methods and tools used to understand digital identities from the fields of anthropology and data science. This includes examining differing approaches to ethics in these fields. The course will also explore theories about identity and different ways identities are constructed and performed through digital technologies, such as social media, internet cultures, and fitness trackers. We will also explore the identities of those who design and build these technologies, the politics and norms reproduced through technologies themselves, and the effects they have with particular attention to the role of gender and race. Finally, we will consider the political economic contexts of these technologies and the formation of digital identities.


The teaching in spring 2021 will be online until the 1. of April due to the Covid19 situation.

As soon as it is permitted and justifiable, it is up to the individual lecturer whether to transition to a blended format or wish to continue with full online teaching for the rest of the semester.

The individual lecturer will inform you of the above choice in the Absalon room for each course.

Courses with oral exams will be held online if the relevant restrictions have not been lifted at least four weeks before the individual exam. This will be notified in Absalon.

Courses with written exams will not experience any changes in relation to the normal exam form.

Learning outcome


  • Describe methods and practices relating to data science
  • Identify purposes and values of different forms of data
  • Understand and reflect on different theories and cases relating to identities and digital technologies



  • Reflect on the social effects and contexts of digital data and technologies in relation to aspects of identity, such as selfhood, gender, race, and class
  • Apply research strategies from digital anthropology and tools from data science
  • Analyze the ethical implications of methodological practices for research about and using digital technologies



  • Conduct analyses of digital identities using methods and tools from anthropology and data science
  • Critically reflect on these methods, the relationship between digital technologies and identities, and their social effects
  • Reflect on the role of anthropology in relation to digital data and technologies



The teaching is on campus during autumn semester 2020. However, due to the covid19 situation all classes are available online too for students who are not able to attend classes on campus because of their covid-19 risk.

Always remember to check Absalon for the latest updates.

BSc students and MSc students: 500 pages obligatory literature

The teacher will publish 200-300 pages of supplementary literature.

Course literature will be available through Absalon.

Continuous feedback during the course of the semester
7,5 ECTS
Type of assessment
Written assignment
Essay length: 21,600–26,400 keystrokes for an individual submission. 6,750–8,250 keystrokes per extra member for group submissions. The maximum number of students who can write an essay in a group is four.
For groups writing together it must be clearly indicated which parts of the assignment each of the students has written.
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship
Criteria for exam assessment

See description of learning outcome. Formalities for Written Works must be fulfilled, read more: MSc Students/ BA students (in Danish)/ exchange and credit students 

  • Category
  • Hours
  • Lectures
  • 42
  • Preparation
  • 133
  • Exam
  • 35
  • English
  • 210