oai:arXiv.org:2405.00129
Computer Science
2024
10/16/2024
Network scientists often use complex dynamic processes to describe network contagions, but tools for fitting contagion models typically assume simple dynamics.
Here, we address this gap by developing a nonparametric method to reconstruct a network and dynamics from a series of node states, using a model that breaks the dichotomy between simple pairwise and complex neighborhood-based contagions.
We then show that a network is more easily reconstructed when observed through the lens of complex contagions if it is dense or the dynamic saturates, and that simple contagions are better otherwise.
;Comment: 8 pages, 5 figures
Landry, Nicholas W.,Thompson, William,Hébert-Dufresne, Laurent,Young, Jean-Gabriel, 2024, Reconstructing networks from simple and complex contagions