Program Overview
Program Overview
The University of Copenhagen offers a Master's program in Social Data Science, which includes a mandatory course, ASDK20005U Social Data Analysis.
Course Description
This course introduces theories, concepts, and methods for the social scientific study of behavior, social networks, and cultural ideas. Through a combination of lectures, seminars, and exercises, the course shows how classic social science problems can be investigated using data science approaches, and how the study of large-scale digital social data can benefit from social science approaches.
Learning Outcomes
At the end of the course, students are able to:
- Account for key social science theories of behavior, networks, and ideas.
- Demonstrate understanding of how social data science approaches can improve social science theories and vice versa.
- Assess the relevance of computational social data science approaches to investigate social data science problems.
- Identify and operationalize relevant theoretical concepts and constructs.
- Perform the conceptual work necessary for social data science projects.
- Apply best practices in operationalizing relevant social data science theories pertaining to behavior, networks, and ideas.
Literature
The course uses book chapters and scientific articles related to the course content. Students may be asked to purchase one or two books for general background.
Teaching and Learning Methods
The course combines lectures introducing central theories and methods of behavior, networks, and ideas, with seminars, including student presentations and group discussions.
Workload
The workload for the course is as follows:
- Lectures: 28 hours
- Class Instruction: 42 hours
- Preparation: 70 hours
- Project work: 46 hours
- Exam: 20 hours
- Total: 206 hours
Assessment
The course is assessed through a home assignment, which consists of four group assignments that must be submitted as prerequisites to register for the exam. Three out of the four assignments must be approved for the student to participate in the exam. The final exam can be written alone or in groups of up to four students.
Exam Details
- Credit: 7.5 ECTS
- Type of assessment: Home assignment
- Length of home assignment: 15 pages
- Aid: All aids allowed, including ChatGPT and other large language model tools, which must be cited and described in the submitted exam.
- Marking scale: 7-point grading scale
- Censorship form: External censorship
Course Information
- Language: English
- Course code: ASDK20005U
- Credit: 7.5 ECTS
- Level: Full Degree Master
- Duration: 1 block
- Placement: Autumn and Block 2
- Study board: Social Data Science
- Contracting department: Social Data Science
- Contracting faculty: Faculty of Social Sciences
Course Coordinators
- Yani Kartalis
Timetable
The course is scheduled as follows:
- 25E-;CLASS I;;Social Data Analysis
- 25E-;CLASS II;;Social Data Analysis
- 25E-;CLASS III;;Social Data Analysis
Program Details
The Master's program in Social Data Science at the University of Copenhagen is designed to provide students with knowledge about central methodologies and theories of social data science research, and with the capacity to operationalize these. The program includes a range of courses, including ASDK20005U Social Data Analysis, which is a mandatory course for students enrolled in the program. The program is offered in English and is designed to be completed in one block. The program is accredited by the Faculty of Social Sciences and is taught by experienced faculty members. The program is designed to provide students with a comprehensive understanding of social data science and its applications, and to prepare them for careers in research, industry, or government.