People's opinions evolve with time as they interact with their friends, family, colleagues, and
others. In the study of opinion dynamics on networks, one often encodes interactions …

People's opinions change with time as they interact with each other. In a bounded-
confidence model (BCM) of opinion dynamics, individuals (which are represented by the …

Individuals who interact with each other in social networks often exchange ideas and
influence each other's opinions. A popular approach to study the spread of opinions on …

We study a nonlinear bounded-confidence model (BCM) of continuous-time opinion
dynamics on networks with both persuadable individuals and zealots. The model is …

Most opinion dynamics models are based on pairwise interactions. However in many real
situations, discussions take place within groups of people. Here, we define a higher order …

We study a tractable opinion dynamics model that generates long-run disagreements and
persistent opinion fluctuations. Our model involves an inhomogeneous stochastic gossip …

We study transient behavior of gossip opinion dynamics, in which agents randomly interact
pairwise over a weighted graph with two communities. Edges within a community have …

A fundamental question that arises in the analysis of the noise-based synchronization of
opinion dynamics with bounded confidence (BC) is what opinion structures can be …

We consider a variation of the Deffuant-Weisbuch model introduced by Deffuant et al. in
2000, to provide new analytical insights on the opinion dynamics in a social group. We …

In this chapter, we derive and analyse models for consensus dynamics on hypergraphs. As
we discuss, unless there are nonlinear node interaction functions, it is always possible to …