Dynamics over Signed Networks
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Abstract (arXiv)
A signed network is a network with each link associated with a positive or negative sign. Models for nodes interacting over such signed networks, where two different types of interactions take place along the positive and negative links, respectively, arise from various biological, social, political, and economic systems. As modifications to the conventional DeGroot dynamics for positive links, two basic types of negative interactions along negative links, namely the opposing rule and the repelling rule, have been proposed and studied in the literature. This paper reviews a few fundamental convergence results for such dynamics over deterministic or random signed networks under a unified algebraic-graphical method. We show that a systematic tool of studying node state evolution over signed networks can be obtained utilizing generalized Perron-Frobenius theory, graph theory, and elementary algebraic recursions.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Jun 2017.
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Citing papers per year: 2023: 2; 2024: 2; 2025: 2; 2026: 2.
8 papers.
- 2024LLM-based multi-agent poetry generation in non-cooperative environmentscited by 15
- 2023Signed Graph Neural Ordinary Differential Equation for Modeling Continuous-time Dynamicscited by 8
- 2024Large Language Models can Achieve Social Balancecited by 5
- 2025A Signed Graph Approach to Understanding and Mitigating Oversmoothing in GNNscited by 2
- 2025Weaver: Kronecker Product Approximations of Spatiotemporal Attention for Traffic Network Forecastingcited by 1
- 2026Energy-Based Dynamical Models for Neurocomputation, Learning, and Optimizationcited by 1
- 2023Joint Learning of Network Topology and Opinion Dynamics Based on Bandit Algorithmscited by 0
- 2026Exploring Oversmoothing with Householder Matricescited by 0
- 2026Exploring Oversmoothing with Householder Matrices12 Aug 2026
- 2026Energy-Based Dynamical Models for Neurocomputation, Learning, and Optimization6 Apr 2026
- 2025Weaver: Kronecker Product Approximations of Spatiotemporal Attention for Traffic Network Forecasting12 Nov 2025
- 2025A Signed Graph Approach to Understanding and Mitigating Oversmoothing in GNNs17 Feb 2025
- 2024Large Language Models can Achieve Social Balance5 Oct 2024
- 2024LLM-based multi-agent poetry generation in non-cooperative environments5 Sep 2024
- 2023Signed Graph Neural Ordinary Differential Equation for Modeling Continuous-time Dynamics18 Dec 2023
- 2023Joint Learning of Network Topology and Opinion Dynamics Based on Bandit Algorithms25 Jun 2023