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Adding Social Structure to Diffusion Models

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  • DAVID STRANG

    (University of Iowa)

Abstract

Most diffusion models make the implausible assumption that diffusion is unstructured by relationships within the population of interest. This article proposes methods for incorporating a priori notions about social structure into analysis. Diffusion is modeled within an event history framework where the individual's rate of adoption is a function of prior adoptions by related actors. Two diffusion models are suggested: an epidemic model where adoption rates vary with the number of prior adoptions, and a salience model where adoption rates vary with time since the last event. This approach is illustrated in an examination of the decolonization of British and French colonies. Diffusion is shown to occur within regions rather than within empires or the world system as a whole.

Suggested Citation

  • David Strang, 1991. "Adding Social Structure to Diffusion Models," Sociological Methods & Research, , vol. 19(3), pages 324-353, February.
  • Handle: RePEc:sae:somere:v:19:y:1991:i:3:p:324-353
    DOI: 10.1177/0049124191019003003
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    Cited by:

    1. Verstraeten, Soraya P.A. & van Oers, Hans A.M. & Mackenbach, Johan P., 2016. "Decolonization and life expectancy in the Caribbean," Social Science & Medicine, Elsevier, vol. 170(C), pages 87-96.
    2. Christoph Engel & Alon Klement & Karen Weinshall Margel, 2017. "Diffusion of Legal Innovations: The Case of Israeli Class Actions," Discussion Paper Series of the Max Planck Institute for Research on Collective Goods 2017_11, Max Planck Institute for Research on Collective Goods, revised Jan 2018.
    3. Thomas Ambrosio & Jakob Tolstrup, 2019. "How do we tell authoritarian diffusion from illusion? Exploring methodological issues of qualitative research on authoritarian diffusion," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(6), pages 2741-2763, November.
    4. Norman Braun & Henriette Engelhardt, 2002. "Diffusion processes and event history analysis," MPIDR Working Papers WP-2002-007, Max Planck Institute for Demographic Research, Rostock, Germany.
    5. Mushkin, I. & Solomon, S., 2017. "The Inverse Contagion Problem (ICP) vs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 516-531.
    6. Maureen Boyce & Mark Byrne & Erin Dorpinghaus & D. S. Malik & John N. Mordeson, 2016. "Diffusion in Networks: The Strategic Spread of Islamism," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 12(02), pages 113-133, July.
    7. Torben Heinze, 2011. "Mechanism-Based Thinking on Policy Diffusion. A Review of Current Approaches in Political Science," KFG Working Papers p0034, Free University Berlin.
    8. Osei-Owusu, Alexander, 2015. "The Analysis of the Ghana Telecom Industry," 26th European Regional ITS Conference, Madrid 2015 127172, International Telecommunications Society (ITS).
    9. Philip Schleifer & Matteo Fiorini & Graeme Auld, 2017. "Transparency in Transnational Sustainability Governance: A Multivariate Analysis of Regulatory Standard-Setting Programs," RSCAS Working Papers 2017/16, European University Institute.

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