Over the past decade, there has been a growing public fascination with the complex “connectedness” of networks. This connectedness is found in ubiquitous situations: in the rapid growth of the Internet, in the ease with which global communication now takes place, and in the ability of news and misinformation as well as financial and political crises to spread around the globe.
To adequately capture and understand such phenomena, network analysis has proven to be extremely useful. In this context, methodological research on network analytical models picked up a lot of traction in recent years, due to the growing need for ways to handle network data.
This workshop intends to provide interested scholars with an overview of different research strains in the field of network data analysis.
In particular, we will work with data relating to international political interactions, such as the international trade of weapons, migration, and conflicts but also with classical social network data.
Participants will be introduced to the analysis of network data from both a substantive and statistical perspective. In a hands-on session, you will learn to analyze a real-world network dataset through the use of existing, readily available software packages.
About the Instructors
While Giacomo De Nicola is a research assistant and doctoral student at the Institute of Statistics at LMU Munich, Cornelius Fritz is a postdoctoral fellow at Penn State, focusing mainly on developing novel data analysis techniques by combining statistical and machine learning with solid theoretical foundations. Göran Kauermann has been a full professor of Statistics at LMU Munich since 2011 and heads the chair for Statistics in Economics, Business, and Social Sciences there. Additionally, he serves as the chairman of the German Data Science Society (GDS).