{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,29]],"date-time":"2025-11-29T08:01:40Z","timestamp":1764403300402,"version":"3.40.5"},"reference-count":40,"publisher":"Wiley","license":[{"start":{"date-parts":[[2023,9,26]],"date-time":"2023-09-26T00:00:00Z","timestamp":1695686400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2023,9,26]]},"abstract":"<jats:p>The topological structure of the world air transportation network has been the subject of much research. However, to better understand the reality of air networks, one can consider the traffic, the number of passengers, or the distance between flights. This paper studies the weighted world air transportation network through the component structure, recently introduced in the network literature, by using the number of flights. The component structure is based on the community or multiple core-periphery structures and splits the network into local and global components. The local components capture the regional flights of these two mesoscopic structures (dense parts). The global components capture the inter-regional flights (links between the dense parts). We perform a comparative analysis of the world air transportation network and its components with their weighted counterparts. Moreover, we explore the strength and the s-core of these networks. Results display fewer local components well delimited and more global components covering the world than the unweighted world air transportation network. Centrality analysis reveals the difference between the top airports with high traffic and the top airports with high degrees. This difference is more pronounced in the global air network and the largest global component. Core analysis shows similitude between the s-core and the k-core for the local and global components, even though the latter includes more airports. For the world air network, the North and Central America-Caribbean airports dominate the s-core, whereas the European airports dominate the k-core.<\/jats:p>","DOI":"10.1155\/2023\/3411799","type":"journal-article","created":{"date-parts":[[2023,9,26]],"date-time":"2023-09-26T20:05:07Z","timestamp":1695758707000},"page":"1-29","source":"Crossref","is-referenced-by-count":2,"title":["Exploring the Regional Structure of the Worldwide Air Traffic and Route Networks"],"prefix":"10.1155","volume":"2023","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5624-319X","authenticated-orcid":true,"given":"Issa Moussa","family":"Diop","sequence":"first","affiliation":[{"name":"LACCA Lab, Gaston Berger University, Saint-Louis, Senegal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6606-7337","authenticated-orcid":true,"given":"Cherif","family":"Diallo","sequence":"additional","affiliation":[{"name":"LACCA Lab, Gaston Berger University, Saint-Louis, Senegal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1619-7998","authenticated-orcid":true,"given":"Chantal","family":"Cherifi","sequence":"additional","affiliation":[{"name":"DISP Lab, University of Lyon 2, Lyon, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9124-4921","authenticated-orcid":true,"given":"Hocine","family":"Cherifi","sequence":"additional","affiliation":[{"name":"LIB EA 7534, University of Burgundy Franche-Comt\u00e9, Dijon, France"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1016\/j.physrep.2021.10.005"},{"first-page":"21","article-title":"Power grids as complex net- works: topology and fragility","author":"M. 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