Modeling the world-wide airport network

By Roger Guimerà, Luís A. Nunes Amaral. 2004

464 citations recorded by the source corpus.

Subfields: Statistical and Nonlinear Physics, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/d039c0c31d4396eaa5bb0d8b0baeb24d84a41d40

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In Statistical and Nonlinear Physics

In Strategy and Management

Citations in the corpus

Analyzing and modeling real-world phenomena with complex networks: a survey of applications (2007, methodology): “The worldwide airport network [16, 252] is a scale-free, sma ll-world network.”
Applying social network analysis in economic geography: framing some key analytic issues (2009, background): “This implies we are not considering potential applications of network theory in other topics in economic geography, such as urban systems and infrastructure networks (Guimera and Amaral 2004).”
Exploring the structure of the U.S. intercity passenger air transportation network: a weighted complex network approach (2008, methodology): “For example, different values on rc or different decay functions could produce network with different degree of assortaticity and clustering (Barrat et al. 2005; Guimera and Amaral 2004 ).”
Characterization of complex networks: A survey of measurements (2005, background): “This kind of network exhibits a power law behavior as described in [173, 62].”
Analysis of the airport network of India as a complex weighted network (2004, background): “During the past few years, complex network analysis has been used to study transportation systems (railways [17] and airlines [2,9,10,4,8,21]), which are man-made infrastructures – from different aspects – apart from many other”
Social networks (2009, unknown): “We assume that the central mechanism of the dynamics of ac-quaintance networks is that people are introduced to each other by a common acquaintance ( transitive linking ).”
Uncovering space-independent communities in spatial networks (2010, background): “A crucial diﬀerence stems from the cost associated to long-distance links [4, 5, 6, 7, 8, 9, 10, 11, 12] which restricts the existence of hubs, i.e. high degree nodes, and thus the observation of fat-tailed degree distributions in spatial networks.”
The Power Grid as a Complex Network: a Survey (2011, background): “…has been used in many diﬀerent ﬁelds of knowledge, from biology [7] to chemistry [8], from linguistics to social sciences [9], from telephone call patterns [10] to computer networks [11] and web [12, 13] to virus spreading [14, 15, 16] to logistics [17, 18, 19] and also inter-banking systems [20].”
Exploring the network structure and nodal centrality of China (2011, background): “…edges (m) Average degree (hki) Average path length (L) Clustering coefficient (C) Network structure Bagler (2008) India 79 455 11.52 2.26 0.66 SW Guimerá et al. (2005) World 3883 27,051 13.93 4.4 0.62 SF SW Guida and Maria (2007) Italy 50 310 12.40 1.98 2.14 0.07 0.1 SF SW Fractal Xu and…”
Centrality measures and the importance of generalist species in pollination networks (2010, background): “…distances to the rest of the nodes in the network, as shown in several ecological and non-ecological studies (Dunne et al., 2002; Goh et al., 2002; Guimerà and Amaral, 2004; Hahn and Kerns, 2004; Memmott et al., 2004; Jordán et al., 2006; Lee, 2006; Estrada, 2007); and (ii) nestedness, a…”
High-Betweenness Proteins in the Yeast Protein Interaction Network (2005, methodology): “Betweenness has also been used to characterize the “modularity” (eg, community structure) of various natural and man-made networks (see [12, 13 ]).”