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Modularity Maximization and Tree Clustering: Novel Ways to Determine Effective Geographic Borders

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Handbook of Optimization in Complex Networks

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 57))

Abstract

Territorial subdivisions and geographic borders are essential for understanding phenomena in sociology, political science, history, and economics. They influence the interregional flow of information and cross-border trade and affect the diffusion of innovation and technology. However, most existing administrative borders were determined by a variety of historic and political circumstances along with some degree of arbitrariness. Societies have changed drastically, and it is doubtful that currently existing borders reflect the most logical divisions. Fortunately, at this point in history we are in a position to actually measure some aspects of the geographic structure of society through human mobility. Large-scale transportation systems such as trains and airlines provide data about the number of people traveling between geographic locations, and many promising human mobility proxies are being discovered, such as cell phones, bank notes, and various online social networks. In this chapter we apply two optimization techniques to a human mobility proxy (bank note circulation) to investigate the effective geographic borders that emerge from a direct analysis of human mobility.

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Notes

  1. 1.

    http://www.census.gov.

  2. 2.

    http://www.stanford.edu/~dgleich/programs/matlab_bgl/.

  3. 3.

    http://www.boost.org/doc/libs/1_41_0/libs/graph/doc/index.html.

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Author information

Authors and Affiliations

  1. Northwestern University, Evanston, IL, USA

    D. Grady & D. Brockmann

  2. Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany

    R. Brune & C. Thiemann

  3. Group leader CMB Professor for Mathematics in Systems Biology, Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Ingolstädter Landstraße 1, 85764, Neuherberg, Germany

    F. Theis

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  1. D. Grady
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  4. F. Theis
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  5. D. Brockmann
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Correspondence to D. Brockmann .

Editor information

Editors and Affiliations

  1. Science and Engineering, Department of Computer and Information, University of Florida, Gainesville, 3260, Florida, USA

    My T. Thai

  2. , Department of Industrial & Systems Engin, University of Florida, Weil Hall 401, Gainesville, 32611-6595, Florida, USA

    Panos M. Pardalos

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Grady, D., Brune, R., Thiemann, C., Theis, F., Brockmann, D. (2012). Modularity Maximization and Tree Clustering: Novel Ways to Determine Effective Geographic Borders. In: Thai, M., Pardalos, P. (eds) Handbook of Optimization in Complex Networks. Springer Optimization and Its Applications(), vol 57. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-0754-6_7

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