Structural importance and evolution: An application to financial transaction networks

A fundamental problem in the study of networks is identification important nodes. This typically achieved using centrality metrics, which rank nodes terms their position network. approach works well for static networks, that do not change over time, but does consider dynamics Here we propose instead to measure importance a node based on how much its strength will impact global structure network, spectrum adjacency matrix. We apply our method equity transaction and show that, while it can still be computed from good predictor subsequently transacting. implies representations temporal contain information about dynamics.