Network Topology of the Austrian Airline Flights

TL;DR

This paper analyzes the Austrian airline flight network using complex network theory, revealing small-world features, power-law degree distributions, and hierarchical organization among airports.

Contribution

It provides a detailed quantitative analysis of the flight network, highlighting its small-world properties, degree distribution behaviors, and hierarchical structure, which were not previously characterized.

Findings

The network exhibits small-world features with high clustering and short path lengths.

Degree distributions follow power-law behavior with different regimes.

Large airports tend to connect with smaller airports, indicating disassortative mixing.

Abstract

The information of the Austrian airline flights was collected and quantitatively analyzed by the concepts of complex network. It displays some features of small-world networks, namely large clustering coefficient and small average shortest-path length. The degree distributions of the networks reveal power law behavior with exponent value of 2 $\sim$ 3 for the small degree branch but a flat tail for the large degree branch. Similarly, the flight weight distributions show power-law behavior for the small weight branch. Furthermore, we found that the clustering coefficient $C$, 0.206, of this flight network is greatly larger than that of a random network, 0.01, which has the same numbers of the airports ($N$) and mean degree ($<k>$), and the diameter $D$, 2.383, of the flight network is significantly smaller than the value of the same random network, 18.67. In addition, the degree-degree correlation analysis shows the network has disassortative behavior, i.e. the large airports are likely to link to smaller airports. Furthermore, the clustering coefficient analysis indicates that the large airports reveal the hierarchical organization.