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2018/2019  KAN-CPOLV1022U  Social Network analysis

English Title
Social Network analysis

Course information
Language English
Course ECTS 7.5 ECTS
Type Elective
Level Full Degree Master
Duration One Quarter
Start time of the course First Quarter
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for BSc/MSc i International Business and Politics, MSc
Course coordinator
  • Anton Grau Larsen - Department of Organization (IOA)
  • Lasse Folke Henriksen - Department of Organization (IOA)
Main academic disciplines
  • Methodology and philosophy of science
  • Sociology
  • Statistics and quantitative methods
Teaching methods
  • Face-to-face teaching
Last updated on 06-02-2018

Relevant links
Learning objectives
  • Understand, and critically reflect on, network theory
  • Be able to use and apply network data
  • Be able to evaluate the validity of network data in addressing a research question
  • Be able to depict, interpret and analyse both the structure and the role of actors in a network
Course prerequisites
Knowledge of basic research methods in the social sciences is an advantage. However, Social Network Analysis is a method in its own right and can be learned without any prior training.
Examination
Social Network analysis:
Exam ECTS 7,5
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 15 pages
Assignment type Project
Duration Written product to be submitted on specified date and time.
Grading scale 7-step scale
Examiner(s) One internal examiner
Exam period Autumn
Make-up exam/re-exam
Same examination form as the ordinary exam
Hand in of orginal written product.
Description of the exam procedure

The project report will be handed in at the end of the course. During the course, the student will get the opportunity to work with the network data, for instance data on Danish Corporate Networks and Danish Elite Networks, used in the exam, or to collect, or expand, data on their own. There will be supervision on the methods used in the project report during the course.
Course content and structure

Networks are everywhere: in the organizations we work in, between family members, on the web or between nations and international organisations.  In recent years, understanding networks has become ever more important. From social media and ‘big data’ to the relations forming our everyday life, social network analysis offers a unique way of understanding society. Only our imagination limits what can be seen as a network: you can identify patterns in global mobility by looking at networks of travelers between airports, find the structure in consumption patterns by looking at networks of products bought by the same consumers, or find elite groups by looking at shared board memberships.

 

Being able to understand and analyze networks is important in business management, enabling us to find the logics of cultural phenomena and communication, and to identify structures in political institutions.     

The aim of the course is to introduce social network analysis and network theory, and their basic concepts, in a way that can be applied. In other words: we expect you to, at the end of the course, to be able to both understand how social networks can help us understand the world and to be able to perform such an analysis yourself.


We will start the course by introducing what social network analysis is, including network theory. Second, we will look at what network data is and introduce you to the programs able to handle network data. This will include starting to identify the data that you will use for your research project. Finally, we will go through basic concepts in network analysis and apply them in the analysis of your project report.

 

Our aim is to teach all aspects of network analysis - data collection, network identification, identifying key actors, interpreting and understanding network structure and network plotting - in a hands-on approach, based on your network of interest during classes and exercises. We will provide network data on Danish business and political networks, used in our own research, for interested students.
Description of the teaching methods
The course will use a combination of lectures, introducing network concepts, hands-on exercises, coding of data and analysis, group supervision, and dealing with selecting a case for the project report and applying social network analysis to that case.
Feedback during the teaching period
We will have a final seminar after the grading of exams. Those participating in the seminar will get class and group feedback on their work.
Student workload
Lectures 30 hours
Lectures - exercises 15 hours
Reading literature 106 hours
Exam 65 hours
Expected literature

We will use two main textbooks.

Scott, John. Social Network Analysis : A Handbook. London: Sage, 2000

Wasserman, Stanley, and Katherine Faust. Social Network Analysis: Methods and Applications. Cambridge University Press, 1994.

 

 
Last updated on 06-02-2018