This is the main course website for the seminar Social Network Analysis in winter term 2022/23 at University of Bayreuth.
Recordings accompanying the seminar are available online.
In the seminar, students are asked to work on self-selected research questions using methods of network analysis. The methods are new to the students in that they never worked with them before. That's why the seminar consists of some introductory part in which the methods are presented and their applicability using R is discussed. Students then formulate an appropriate research question, find or create a data set, and apply the newly acquired methods to the data set. After successful participation in this seminar, students are able to understand the most important theoretical and methodological principles of social network analysis and to apply these methods to their own research projects.
In the vast majority of cases, students have had no prior exposure to programming. This means that in the seminar they not only learn to apply the methods for network analysis in R, but often teach themselves basic skills in R as well.
An overview over selected results from previous semesters can be found here: https://mircoschoenfeld.de/seminar-social-network-analysis.html
|Collecting Network Data||
|Reading in Network Data||
|Visualize bipartite networks||
|Project bipartite networks||
|Obtain centrality metrics||
|Components in networks||
|Filter networks based on attributes||
|Analyze a real-world social network dataset||
|Find a video here|
|Find code material here|
|Find external material here|
- Marina Hennig, Ulrik Brandes, Jürgen Pfeffer, and Ines Mergel. Studying social networks: A guide to empirical research. Campus Verlag, 2012.