Node Centrality

Node centrality measures the relative importance of nodes within a network, aiming to identify influential or critical points. Current research focuses on improving centrality calculations for complex network structures, including signed networks and those exhibiting core-periphery organization, often employing graph neural networks (GNNs) and random walk algorithms to address computational challenges and biases in existing methods. These advancements have implications for diverse fields, enhancing the accuracy of community detection, link prediction, and the understanding of information diffusion in various systems, from social networks to biological systems and decentralized machine learning.