Social Network Analysis Visualization by MartinGrandjean CC BY-SA 3.0

Enrol
14.2.2019 at 09:00 - 12.3.2019 at 23:59

Timetable

Here is the course’s teaching schedule. Check the description for possible other schedules.

DateTimeLocation
Tue 12.3.2019
12:15 - 13:45
Tue 19.3.2019
12:15 - 13:45
Tue 26.3.2019
12:15 - 13:45
Tue 2.4.2019
12:15 - 13:45
Tue 9.4.2019
12:15 - 13:45
Tue 16.4.2019
12:15 - 13:45
Thu 25.4.2019
14:15 - 15:45
Mon 29.4.2019
12:15 - 13:45

Description

Open to students of the Master’s Programme in Contemporary Societies, Society and Change, and Global Politics and Communication.

After completing the course, students will understand the profound, but also unexpected ways in which datafication affects various domains of research and everyday life. Students will have learned the vocabulary of datafication, and they will be able to contrast and compare the different strands of research and critically evaluate the speculative and promissory aspects of datafication. In the course of reading the literature and engaging with it, students will learn oral presentation skills, group discussion skills and academic writing.

The capacity to collect, store and analyse physiological, behavioural and geo-locational data has come to affect a wide array of everyday life domains, from policy-making to policing, corporate marketing to education, health to urban planning. This course explores how researchers in sociology, science and technology studies, anthropology and media studies have responded to the big data paradigm shift and begun to explore “datafication”, understood as the conversion of qualitative aspects of life into quantified data. The literature reviewed during the course focuses on “data power”, covering questions related to economic exploitation, surveillance and biopolitics. The second area of research “living with data” covers themes such as data practices and data sociality, or self-fashioning through data. The third area of research focuses on “data-human mediation”, which takes into account the nonhuman elements (devices, algorithms, data infrastructure and the data itself) that mediate power dynamics and individual and social experiences. The course concludes by introducing how scholars have begun to experiment with alternative big data logics, applied forms of research and data activism.

The literature will be provided during the course.

Graded on a scale of 0 to 5 (0 = Fail, 1 = Passable, 2 = Satisfactory, 3 = Good, 4 = Very Good, 5 = Excellent)

The course is a lecture course, with student presentations reviewing the covered literature. In addition, an essay will be written as a final assignment.