Cooperative opinion dynamics on multiple interdependent topics: Modeling and analysis

Abstract

To model the interdependent couplings of multiple topics, we develop a set of rules for opinion updates of a group of agents. The rules are used to design or assign values to the elements of interdependent weighting matrices. The cooperative and anti-cooperative couplings are modeled in both the inverse-proportional and proportional feedbacks. The behaviors of cooperative opinion dynamics are analyzed using a null space property of state-dependent matrix-weighted Laplacian matrices and a Lyapunov candidate. Various consensus properties of state-dependent matrix-weighted Laplacian matrices are predicted according to the intra-agent network topology and inter-dependency topical coupling topologies.

References in corpus (3)

• Theory and Applications of Matrix-Weighted Consensus
• Evolution of Social Power in Social Networks with Dynamic Topology
• Continuous-time Opinion Dynamics on Multiple Interdependent Topics

Cited by in corpus (6)

• Recent advances in opinion propagation dynamics: A 2020 Survey
• Discrete-Time Matrix-Weighted Consensus
• Randomized Matrix Weighted Consensus
• Differential Game Strategies for Social Networks with Self-Interested Individuals
• A Game Approach to Multi-dimensional Opinion Dynamics in Social Networks with Stubborn Strategist Agents
• Leader-Driven Opinion Dynamics in Signed Social Networks With Asynchronous Trust/Distrust Level Evolution