Most real‐world networks are both dynamic and multivariate in nature, meaning that the
network is associated with various attributes and both the network structure and attributes …

With the growing popularity of Non-Fungible Tokens (NFT), a new type of digital assets,
various fraudulent activities have appeared in NFT markets. Among them, wash trading has …

Massive sequence view (MSV) is a classic timeline-based dynamic network visualization
approach. However, it is vulnerable to visual clutter caused by overlap** edges, thereby …

The dynamic network visualization design space consists of two major dimensions: network
structural and temporal representation. As more techniques are developed and published, a …

Networks are often used to model the structure of interactions between parts of a system.
One important characteristic of a network is the so-called network community structures that …

Many algorithms have been proposed in the last 10 years for the discovery of dynamic
communities. However, these methods are seldom compared between themselves. In this …

The visual analysis of multivariate network data is a common yet difficult task in many
domains. The major challenge is to visualize the network's topology and additional attributes …

Temporal (or time-evolving) networks are commonly used to model complex systems and
the evolution of their components throughout time. Although these networks can be …

Visualizing relational data is crucial for understanding complex connections between
entities in social networks, political affiliations, or biological interactions. Well-known …

Temporal networks have been used to map the structural evolution of social, technological,
and biological systems, among others. Due to the large amount of information on real-world …