Our competence centre researches how information and influences spread within networks and how these processes can be specifically curbed or promoted.
Many social, economic, or technical systems from the real world can be modelled as networks. Such networks enable mathematical modelling and statistical analysis of network effects, such as those that occur in the spread of diseases, fake news, or innovations.
Overview
The Social Network Analysis Competence Centre brings together experts with broad-based expertise in economics, data science, mathematics and statistics. What unites us is a keen interest in networks and the multitude of challenges that can be solved with the help of network analysis.
A central focus of our Competence Centre is the study of epidemic processes. We develop data-driven methods for the early containment of such processes. However, the scope of this research is not limited to diseases: it is equally relevant to social contagion effects, for example in connection with fake news, innovation or marketing (e.g. for identifying influential actors in networks).
With our applied research, we aim to solve practical problems. The goal of each project is to translate the results into practice, because only then can our research ultimately have a tangible impact.
Service offerings
We are happy to assist researchers, organisations and companies with methodological questions on the following topics:
Machine learning (on networks)
- Graph Neural Networks
- Gaussian processes and Bayesian optimisation
- Recommender Systems
Network structure and representation
- Static and temporal network representations
- Visualisation of networks
- Identification of communities in networks
Analysis of key players
- Centrality metrics, PageRank, etc.
- Influence Maximisation
Dynamics and simulation on networks
- Monte Carlo simulations on networks
Dynamic processes on networks (epidemics, random walks, etc.)
Team
Contact
Dr. Martin Sterchi
- Phone
- +41 62 957 24 18
- martin.sterchi@fhnw.ch