Document detail
ID
oai:arXiv.org:2405.00129
Topic
Computer Science - Social and Info... Quantitative Biology - Populations... Statistics - Machine LearningAuthor
Landry, Nicholas W. Thompson, William Hébert-Dufresne, Laurent Young, Jean-GabrielCategory
Computer Science
Year
2024
listing date
10/16/2024
Keywords
network contagionsAbstract
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
