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An Overview of the Measurement of Segregation: Classical Approaches and Social Network Analysis

In: Complex Networks and Dynamics

Author

Listed:
  • Antonio Rodriguez-Moral

    (Universidad Nacional de Educación a Distancia (UNED))

  • Marc Vorsatz

    (Universidad Nacional de Educación a Distancia (UNED)
    Fundación de Estudios de Economía Aplicada (FEDEA))

Abstract

We present a comprehensive overview of the literature on the measurement on segregation. With a focus on the evenness and exposure dimensions—two of the five dimensions of segregation in the multi-dimensional framework defined by Massey and Denton (Soc Forces 67(2):281–315, 1988)—we introduce some of the most relevant segregation measures developed under the classical statistical approach and under the social networks analysis framework. We also briefly describe two different approaches for the definition of segregation measures when using social networks, namely the use of descriptive graph statistics and the use of spectral graph theory.

Suggested Citation

  • Antonio Rodriguez-Moral & Marc Vorsatz, 2016. "An Overview of the Measurement of Segregation: Classical Approaches and Social Network Analysis," Lecture Notes in Economics and Mathematical Systems, in: Pasquale Commendatore & Mariano Matilla-García & Luis M. Varela & Jose S. Cánovas (ed.), Complex Networks and Dynamics, pages 93-119, Springer.
    • Handle: RePEc:spr:lnechp:978-3-319-40803-3_5
    DOI: 10.1007/978-3-319-40803-3_5
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    Cited by:

    1. Sandro Sousa & Vincenzo Nicosia, 2022. "Quantifying ethnic segregation in cities through random walks," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    2. Hoffmann, Till & Jones, Nick S., 2020. "Inference of a universal social scale and segregation measures using social connectivity kernels," MPRA Paper 103852, University Library of Munich, Germany.
    3. Lee, Shu En & Lim, Jing Zhi & Shen, Lucas, 2021. "Segregation Across Neighborhoods in a Small City," MPRA Paper 115301, University Library of Munich, Germany.

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