Subgraphs and motifs in a dynamic airline network
arXiv:1807.02585
Abstract
How does the small-scale topological structure of an airline network behave as the network evolves? To address this question, we study the dynamic properties of small undirected subgraphs using 15 years of data on Southwest Airlines' domestic route service. We use exact enumeration formulae to identify statistically over- and under-represented subgraphs, known as motifs and anti-motifs. We discover substantial topology transitions in Southwest's network and provide evidence for time-varying power-law scaling between subgraph counts and the number of edges in the network. We also suggest a node-ranking measure that can identify important nodes relative to specific local topologies. Our results extend the toolkit of subgraph-based methods and provide new insight into transportation networks and the strategic behaviour of firms.
arXiv comment41 pages, 17 figures
References in corpus (15)
- The structure and function of complex networks
- The architecture of complex weighted networks
- Self-similarity of complex networks
- Subgraph Centrality in Complex Networks
- Random graphs with clustering
- Self-similarity of complex networks and hidden metric spaces
- Spectral Measures of Bipartivity in Complex Networks
- Subgraphs in random networks
- Topological Generalizations of network motifs
- Methods for estimating the size of Google Scholar
- Resilience and rewiring of the passenger airline networks in the United States
- Coarse-Graining and Self-Dissimilarity of Complex Networks
- Emergence of core-peripheries in networks
- Subgraphs and network motifs in geometric networks
- Cliques and a new measure of clustering: with application to U.S. domestic airlines