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Complex Networks

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Encyclopedia of Big Data

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In recent years, the emergence of a large amount of data dispersed in several types of databases enabled the extraction of information on a never seen scale. Complex networks allow the connection of a vast amount of scattered and unstructured data in order to understand relations, construct models for their interpretation, analyze structures, detect patterns, and predict behaviors.

The study of complex networks is multidisciplinary and covers several knowledge areas as computer science, physics, mathematics, sociology, and biology. Within the context of the Theory of Complex Networks, a network is a graph that represents a set of nodes connected by edges, which together form a network. This network or graph can represent relationships between objects/agents. Graphs can be used to model many types of relations and processes in physical, biological, social, and information systems.

A graph is a graphical representation of a pattern of relationships and is used to reveal and quantify...

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Further Readings

  • Barabási, A.-L. (2003). Linked. Cambridge, MA: Perseus Publishing.

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  • Barabási, A.-L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509.

    Article  Google Scholar 

  • Bentley, R. A., O’Brien, M. J., & Brock, W. A. (2014). Mapping collective behavior in the big-data era. Behavioral and Brain Sciences, 37, 63.

    Article  Google Scholar 

  • Boccaletti, S., et al. (2006). Complex networks: Structure and dynamics. Physics Reports, 424(4–5), 175.

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  • McKelvey, K., et al. (2012). Visualizing communication on social media: Making big data accessible. arXiv preprint arXiv:1202.1367.

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  • Strogatz, S. H. (2001). Exploring complex networks. Nature, 410(6825), 268.

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  • Watts, D. (2003). Six degrees: The science of a connected age. New York: Norton.

    Google Scholar 

  • Watts, D. (2004). The “new” science of networks. Annual Review of Sociology, 30(1), 243.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. University of Minho, Braga, Minho, Portugal

    Ines Amaral

  2. Instituto Superior Miguel Torga, Coimbra, Portugal

    Ines Amaral

Authors
  1. Ines Amaral
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Correspondence to Ines Amaral .

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Editors and Affiliations

  1. School of Policy, Government and International Affairs, George Mason University, Fairfax, Virginia, USA

    Laurie A. Schintler

  2. School of Policy, Government and International Affairs, George Mason University, Fairfax, Virginia, USA

    Connie L. McNeely

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Amaral, I. (2018). Complex Networks. In: Schintler, L., McNeely, C. (eds) Encyclopedia of Big Data. Springer, Cham. https://doi.org/10.1007/978-3-319-32001-4_40-1

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  • DOI: https://doi.org/10.1007/978-3-319-32001-4_40-1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32001-4

  • Online ISBN: 978-3-319-32001-4

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