The transsortative structure of networks
Abstract
Network topologies can be highly non-trivial, due to the complex underlying behaviours that form them. While past research has shown that some processes on networks may be characterized by local statistics describing nodes and their neighbours, such as degree assortativity, these quantities fail to capture important sources of variation in network structure. We define a property called transsortativity that describes correlations among a node’s neighbours. Transsortativity can be systematically varied, independently of the network’s degree distribution and assortativity. Moreover, it can significantly impact the spread of contagions as well as the perceptions of neighbours, known as the majority illusion. Our work improves our ability to create and analyse more realistic models of complex networks.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- May 01, 2020
- Source ID
- 10.1098/rspa.2019.0772
Entities
People
- Allon G. Percus
- Keith Burghardt
- Kristina Lerman
- Shin-chieng Ngo
Organizations
- Army Research Office
- Claremont Graduate University
- University of Southern California