Social structures are often represented as networks (or graphs) where nodes (or vertices) represent people and edges (or links) represent their relationships. Social network analysis investigates these networks using graph theory, network science, or graph deep learning.
In this practical course, you can get hands-on experience in this field of research or more specifically in the following areas:
- Python programming by helping us extend our existing software frameworks
- Analysing real-world social structures using graph theory or network science, e.g. collaboration networks from open-source software repositories on GitHub
- Applying graph deep learning methods such as Graph Neural Networks (GNNs)
- Dozent: Moritz Lampert
- Dozent: Lisi Qarkaxhija
- Dozent: Ingo Scholtes