Non-consensus Opinion Models with Unreliable Links
Introduction
Opinion dynamics in social networks have been extensively studied, often under the assumption that individuals eventually reach consensus. However, in many real-world scenarios, opinions do not necessarily converge to a single view, especially when the connections between individuals are unreliable. This leads to non-consensus models, where interactions between individuals, influenced by random or faulty communication links, result in the persistence of diverse opinions. Understanding these dynamics is crucial for applications ranging from political polarization to the spread of misinformation and social influence.
This project explores the dynamics of non-consensus opinion models in networks with unreliable links. By modeling these links as probabilistic or subject to failure over time, we aim to study how unreliable communication affects opinion formation, stability, and the overall structure of belief systems in a network.
Project
The aim of this project is to investigate the behavior of opinion dynamics in non-consensus models under the influence of unreliable or failing communication links. Specifically, the project will focus on:
· Developing or adapting opinion models where network links are subject to failure or random communication errors.
· Studying the long-term dynamics of opinions and how they stabilize (or remain divergent) in networks with unreliable connections.
· Comparing the impact of different types of unreliable links (e.g., random failure, time-varying reliability) on the persistence of opinion diversity.
· Analyzing how network structure influences the sensitivity of the opinion model to unreliable links and determining whether certain network topologies are more robust to communication failures.
Additionally, the project will involve developing a tailored training plan based on your interests and future career aspirations. This plan will help you gain specific skills in network modeling, dynamical systems, and simulation techniques that align with your professional goals.
Key tasks include:
· Developing mathematical and simulation models for opinion dynamics with unreliable links.
· Investigating how the introduction of unreliable communication links alters the convergence or divergence of opinions.
· Studying the role of network topology in mitigating the effects of unreliable communication.
· Verifying the models and hypotheses through simulations and data analysis.
Requirements
This project is ideal for final-stage students in Artificial Intelligence, Computer Science, Mathematics, Electrical Engineering, or related fields. The ideal candidate should have strong programming skills, a background in network science or dynamical systems, and an interest in opinion dynamics or social network analysis. Independence, communication skills, and the ability to work remotely are also important.
To Apply
Contact Xinhan Liu,
References
1. Liu, X., Achterberg, M.A. & Kooij, R. Mean-field dynamics of the non-consensus opinion model. Appl Netw Sci 9, 47 (2024). https://doi.org/10.1007/s41109-024-00656-w
2. Shao J, Havlin S, Stanley HE (2009) Dynamic opinion model and invasion percolation. Phys Rev Lett 103(1):018701
3. Li Q, Braunstein LA, Wang H, Shao J, Stanley HE, Havlin S (2013) Non-consensus opinion models on complex networks. J Stat Phys 151:92–112