Analysis of the Structure and Dynamics of European Flight Networks
We analyze structure and dynamics of flight networks of 50 airlines active in the European airspace in 2017. Our analysis shows that the concentration of the degree of nodes of different flight networks of airlines is markedly heterogeneous among airlines reflecting heterogeneity of the airline busi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-02-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/24/2/248 |
| _version_ | 1797480555652055040 |
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| author | Matteo Milazzo Federico Musciotto Salvatore Miccichè Rosario N. Mantegna |
| author_facet | Matteo Milazzo Federico Musciotto Salvatore Miccichè Rosario N. Mantegna |
| author_sort | Matteo Milazzo |
| collection | DOAJ |
| description | We analyze structure and dynamics of flight networks of 50 airlines active in the European airspace in 2017. Our analysis shows that the concentration of the degree of nodes of different flight networks of airlines is markedly heterogeneous among airlines reflecting heterogeneity of the airline business models. We obtain an unsupervised classification of airlines by performing a hierarchical clustering that uses a correlation coefficient computed between the average occurrence profiles of 4-motifs of airline networks as similarity measure. The hierarchical tree is highly informative with respect to properties of the different airlines (for example, the number of main hubs, airline participation to intercontinental flights, regional coverage, nature of commercial, cargo, leisure or rental airline). The 4-motif patterns are therefore distinctive of each airline and reflect information about the main determinants of different airlines. This information is different from what can be found looking at the overlap of directed links. |
| first_indexed | 2024-03-09T22:01:45Z |
| format | Article |
| id | doaj.art-97213dc5aee6424ea3194eb76d22848a |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-09T22:01:45Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-97213dc5aee6424ea3194eb76d22848a2023-11-23T19:48:20ZengMDPI AGEntropy1099-43002022-02-0124224810.3390/e24020248Analysis of the Structure and Dynamics of European Flight NetworksMatteo Milazzo0Federico Musciotto1Salvatore Miccichè2Rosario N. Mantegna3Dipartimento di Fisica e Astronomia Ettore Majorana, Università degli Studi di Catania, Via S. Sofia 64, I-95123 Catania, ItalyDipartimento di Fisica e Chimica Emilio Segrè, Università degli Studi di Palermo, Viale delle Scienze, Ed. 18, I-90128 Palermo, ItalyDipartimento di Fisica e Chimica Emilio Segrè, Università degli Studi di Palermo, Viale delle Scienze, Ed. 18, I-90128 Palermo, ItalyDipartimento di Fisica e Chimica Emilio Segrè, Università degli Studi di Palermo, Viale delle Scienze, Ed. 18, I-90128 Palermo, ItalyWe analyze structure and dynamics of flight networks of 50 airlines active in the European airspace in 2017. Our analysis shows that the concentration of the degree of nodes of different flight networks of airlines is markedly heterogeneous among airlines reflecting heterogeneity of the airline business models. We obtain an unsupervised classification of airlines by performing a hierarchical clustering that uses a correlation coefficient computed between the average occurrence profiles of 4-motifs of airline networks as similarity measure. The hierarchical tree is highly informative with respect to properties of the different airlines (for example, the number of main hubs, airline participation to intercontinental flights, regional coverage, nature of commercial, cargo, leisure or rental airline). The 4-motif patterns are therefore distinctive of each airline and reflect information about the main determinants of different airlines. This information is different from what can be found looking at the overlap of directed links.https://www.mdpi.com/1099-4300/24/2/248complex networksnetwork motifsclusteringair transportation system |
| spellingShingle | Matteo Milazzo Federico Musciotto Salvatore Miccichè Rosario N. Mantegna Analysis of the Structure and Dynamics of European Flight Networks Entropy complex networks network motifs clustering air transportation system |
| title | Analysis of the Structure and Dynamics of European Flight Networks |
| title_full | Analysis of the Structure and Dynamics of European Flight Networks |
| title_fullStr | Analysis of the Structure and Dynamics of European Flight Networks |
| title_full_unstemmed | Analysis of the Structure and Dynamics of European Flight Networks |
| title_short | Analysis of the Structure and Dynamics of European Flight Networks |
| title_sort | analysis of the structure and dynamics of european flight networks |
| topic | complex networks network motifs clustering air transportation system |
| url | https://www.mdpi.com/1099-4300/24/2/248 |
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