Network science is a cross-disciplinary field that has grown rapidly in recent years. It has gained importance in various disciplines due to its diverse applications, ranging from public health over digital media to transportation and urban planning, as well as the growing number of sources of suitable data. Wherever relational data is available – not only social interactions, but also connections in the power grid or traffic flows between cities – network analysis provides a useful set of tools for describing, modeling and visualising these kinds of datasets. In this course, we will cover the basic mathematical framework for describing such data, which has its roots in graph theory. We will then move on to computational methods for analysing and modeling larger datasets, while illustrating them with practical examples from various domains of application, both scientific and from public policy. All of this will be accompanied by actual practice using state-of-the-art programming and visualisation tools.
This course is for 2nd year MIA,MPP and MDS students only.
