The analysis and control of large-population systems is of great interest to diverse areas of
research and engineering, ranging from epidemiology over robotic swarms to economics …

A strategy to assist visualization and analysis of large and complex datasets is
dimensionality reduction, with which one maps each data point into a low-dimensional …

Increasing amounts of data are available on temporal, or time-varying, networks. There have
been various representations of temporal network data each of which has different …

The aim of this paper is to derive macroscopic equations for processes on large co-evolving
networks, examples being opinion polarization with the emergence of filter bubbles or other …

We provide a well-posedness theory for a class of nonlocal continuity equations on co-
evolving graphs. We describe the connection among vertices through an edge weight …

Traditional models of opinion dynamics, in which the nodes of a network change their
opinions based on their interactions with neighboring nodes, consider how opinions evolve …

Interacting particles on graphs are routinely used to study magnetic behavior in physics,
disease spread in epidemiology, and opinion dynamics in social sciences. The literature on …

In opinion dynamics, how individuals update their opinions has a profound impact on the
final opinion distribution. Though extensive efforts have been made to explore opinion …

Social interactions influence people's opinions. In some situations, these interactions result
in a consensus opinion; in others, they result in opinion fragmentation and the formation of …

In models of opinion dynamics, the opinions of individual agents evolve with time. One type
of opinion model is a bounded-confidence model (BCM), in which opinions take continuous …