Social Networks 1

Graduate Program (& Advanced Certificate) Status

Course Level: 
Master’s
Doctoral
Campus: 
Vienna
Course Open to: 
Students on-site
Remote students
Academic Year: 
2020-2021
Term: 
Fall
US Credits: 
2
ECTS Credits: 
4
Course Code: 
DNDS 6012
Course Description: 

The aim of this course is to give an overview of the key ideas of network science from a social science perspective. The concept of networks has come to pervade modern society, as we routinely make use of online social networking services, as business gets organized into network forms, and as warfare increasingly targets a loose network of combatants. Network science is an emerging interdisciplinary field, which aims at explaining such complex phenomena, emerging from simple principles of making links. Sociological research on the invisible network infrastructures of global finance, the emergence of social movements, or the formation and operation of terrorist groups all demonstrated that a few critical links can lead to dramatic transformations. This course gives an overview of key research findings in these areas, and it also introduces key methods to record, analyze, and visualize network data. Students will be given access to diverse datasets for class purposes.

Learning Outcomes: 

Students taking this course should be able to understand basic concepts and methods from network science. Based on the knowledge they gained on the course, they will be able to critically interpret researches on social network and network science in general.

Assessment: 

Evaluation in the course is primarily based on a short research paper that is either based on datasets discussed in class, or small scale data collection by students. Beyond the research paper students should also prepare an in-class presentation, and participate in class discussions.

Basis of Evaluation:

Research paper: 65%

Class participation: 20%

Presentation: 15%

Prerequisites: 

Basic knowledge of R and Python.