Oslo, Norway

Collecting and Analyzing Big Data

when 29 June 2020 - 3 July 2020
language English
duration 1 week
credits 8 EC
fee NOK 6000

This course is an introduction to collecting and analyzing "big data" for social scientists. Over the last decade, the variety and types of data available to researchers have exploded. This includes not only contemporary data, such as from websites and social media platforms, but also historical data, from digitized interviews to 19th century newspapers. At the same time, analytic techniques from computer science are increasingly being used to solve social science problems.

Course leader

Associate Professor Neal Caren, Department of Sociology, The University of North Carolina, Chapel Hill, USA

Target group

PhD students or researchers from any social science field of study or related disciplines.

Course aim

One week is not enough time to master the techniques for collecting and analyzing big data. You will, however, be able to establish the foundation for developing these skills. The course is designed as a practical overview. The emphasis each class will be on applying the specific techniques rather than on their mathematical basis. The course will provide an overview in that each lesson will introduce a new method in order to demonstrate the range of methods. Combined, students will have the skills and resources to apply these methods to theoretically-relevant problems in the social sciences.

Credits info

8 EC
A completed course including submission of an approved paper is awarded 8 ECTS.

Fee info

NOK 6000: The participation fee includes:
Daily lunch during the course week(s).
Some social arrangements after class sessions.
Partial covering of expenses towards administration and honorarium for lecturers.
Some parts of the reading material (electronic files) sent to you in advance of the course.

Scholarships

Oslo Summer School for Social Sciences does not have any grants or scholarships. All costs in relation to participation in our courses must be paid by participants themselves, or by their institution.