Information Diffusion

Information diffusion studies how information spreads through networks, aiming to predict its reach and impact. Current research focuses on developing sophisticated models, including graph neural networks, ordinary differential equations, and agent-based simulations, to capture the complex temporal dynamics and diverse influencing factors of this process, such as user preferences and network topology. These advancements improve predictions of information popularity, influence maximization, and cascading failures in various contexts, from social media to power grids, offering valuable insights for applications in marketing, public health, and infrastructure management. Furthermore, research increasingly emphasizes fairness and the mitigation of misinformation spread within these diffusion processes.