With the rapid growth of large online social networks, the ability to analyze large-scale social
structure and behavior has become critically important, and this has led to the development …

In the last decade, temporal networks and static and temporal hypergraphs have enabled
modelling connectivity and spreading processes in a wide array of real-world complex …

A directed hypergraph, which consists of nodes and hyperarcs, is a higher-order data
structure that naturally models directional group interactions (eg, chemical reactions of …

Hypergraphs provide a natural way of representing group relations, whose complexity
motivates an extensive array of prior work to adopt some form of abstraction and …

Network visualisation techniques are important tools for the exploratory analysis of complex
systems. While these methods are regularly applied to visualise data on complex networks …

Hyperbolic geometry offers a natural 'focus+ context'for data visualization and has been
shown to underlie real-world complex networks. However, current hyperbolic network …

We present the design and evaluation of HyperStorylines, a technique that generalizes
Storylines to visualize the evolution of relationships involving multiple types of entities such …

Graph theory has provided a powerful modeling foundation for problems in many domains,
but we argue that group interactions are better modeled by hypergraphs. As we work toward …

Hypergraphs are vital in modelling data with higher-order relations containing more than two
entities, gaining prominence in machine learning and signal processing. Many hypergraph …

Quantitative and qualitative data derived from the analysis of genomes, genes, proteins or
metabolites from tissue or cells are currently generated in huge volumes during biomedical …