Complex Networks Analysis of Commuting

Andrea Montis, Alessandro Chessa, Michele Campagna, Simone Caschili and Giancarlo Deplano
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Andrea Montis: Università degli Studi di Sassari
Michele Campagna: Università degli Studi di Sassari
Simone Caschili: Università degli Studi di Sassari
Giancarlo Deplano: Università degli Studi di Sassari

Chapter Chapter 17 in Complexity and Spatial Networks, 2009, pp 239-255 from Springer

Abstract: Abstract The emerging new science of networks is providing an elegant paradigm for the characterization of the broad area of complex systems. New research perspectives have been opened in the study of many real phenomena and processes, and recently fields like urban, regional, and environmental sciences have gained new insights from the tools provided by network science. The complex networks analysis (CNA) becomes a useful framework in these fields to disentangle problems of a complex and unpredictable nature. At the end of the last millennium, the availability of large data sets and the parallel explosion of computer processing power have made a systematic and intensive application of CNA to the study of very large networks(Pastor-Satorras and Vespignani 2004; Albert and Barabási 2002) possible. According to CNA, complex behaviours are signalled by the emergence of some characteristics that can be featured in terms of statistical properties.

Keywords: Cluster Coefficient; Community Detection; Weighted Network; Preferential Attachment; Real World Phenomenon (search for similar items in EconPapers)
Date: 2009
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DOI: 10.1007/978-3-642-01554-0_17

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