Voter Model

Voter models are mathematical frameworks used to study opinion dynamics and consensus formation in various systems, from social networks to political elections. Current research focuses on extending the basic voter model to incorporate more realistic features, such as context-dependent opinion adoption, the impact of group interactions, and the robustness of these models to malicious influences like backdoor attacks in federated learning. These advancements are improving the accuracy of election forecasting, enhancing the security of machine learning algorithms, and providing deeper insights into the complex processes driving collective decision-making.