The basic interaction unit of many dynamical systems involves more than two nodes. In such situations where networks are not an appropriate modelling framework, it has recently become increasingly popular to turn to higher-order models. In this collection of papers, we derive and analyse models for consensus dynamics on hypergraphs, where nodes interact in groups rather than in pairs.
In many network settings, nodes can be grouped based on heterogeneous characteristics. For example, individuals in social networks differ on certain characteristics such as gender. Group membership can also affect how nodes form connections and thus the network structure, for example through tie formation mechanisms such as homophily. We model the effect of group membership on the documentation and formation of network structure. This allows us to gain a deeper understanding of issues such as inequality and marginalisation through the lens of network analysis.
While the coronavirus spreads around the world, governments are attempting to reduce contagion rates at the expense of negative economic effects. To achieve higher effectiveness with cyclical and fiscal policy measures, it is key to identify the industries that are suffering the most from the unfolding economic crisis. We introduce the CoRisk-Index. It is the first economic indicator of industry-specific risk assessments related to Covid-19.