airports_struc2vec — Air traffic in Brazil, Europe and the USA (struc2vec, 2016)
- Description
Three networks of airports connected by commercial flights in 2016, collected by Ribeiro et al. to evaluate the struc2vec node embedding method, as distributed in their repository:
brazil: airports of Brazil, from the data of the National Civil Aviation Agency (ANAC), from January to December 2016;europe: airports of Europe, from the data of Eurostat, from January to November 2016;usa: airports of the USA, from the data of the Bureau of Transportation Statistics, from January to October 2016.
An undirected edge connects two airports if there were commercial flights between them during the period. Each airport is labeled with its level of activity, by the quartiles of its distribution in each network (so that the four classes have the same size): the number of landings plus takeoffs (Brazil and Europe), or the number of passengers who arrived or departed (USA). The edges are as in the files:
brazilhas 71 self-loops, andeurope2; the numbers of edges thus differ slightly from those stated in the paper (1,038 for Brazil). The data do not identify the airports, except presumably forusa, whose node identifiers look like the airport identifiers of the Bureau of Transportation Statistics.The networks have the following properties:
id: the identifier of the airport in the source data.activity: the activity class of the airport, from 0 (the 25% most active airports) to 3 (the 25% least active ones); the order is not stated by the source, but is evident from the degrees of the airports in each class.
- Tags
- Transportation Airport Unweighted Metadata
- Citation
-
- L. F. R. Ribeiro, P. H. P. Saverese, D. R. Figueiredo, "struc2vec: Learning Node Representations from Structural Identity." Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 385-394 (2017) 10.1145/3097983.3098061 Sci-Hub
- Upstream URL OK
- https://github.com/leoribeiro/struc2vec
- Upstream license
- MIT, https://github.com/leoribeiro/struc2vec/blob/77b4cc63e79a37b1496f340c7772d932038417ec/LICENSE
- Networks
-
Tip: click on a column header to sort the list, or hover over it for a description.
Column legend
- $\left<k\right>$
- Mean degree
- $\sigma_k$
- Standard deviation of the degrees
- $\lambda_h$
- Largest eigenvalue of the Hashimoto (non-backtracking) matrix
- $\tau$
- Random walk mixing time
- $r$
- Degree assortativity
- $c$
- Global clustering coefficient
- $\oslash$
- (Pseudo-) diameter
- $S$
- Relative size of the largest component
- NPs
- Node properties
- EPs
- Edge properties
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv brazil 131 1,074 16.40 17.27 31.47 4.58 -0.20 0.45 4 1.00 Undirected Unipartite id activity 4 KiB 7 KiB 6 KiB 5 KiB europe 399 5,995 30.05 34.65 63.79 3.69 -0.22 0.33 5 1.00 Undirected Unipartite id activity 14 KiB 24 KiB 24 KiB 21 KiB usa 1,190 13,599 22.86 40.45 99.94 42.78 0.03 0.43 8 1.00 Undirected Unipartite id activity 41 KiB 68 KiB 66 KiB 57 KiB - Ridiculograms*