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Diffusion Centrality: Foundations and Extensions

Author

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  • Yann Bramoullé

    (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Garance Genicot

    (Department of Economics, Georgetown University)

Abstract

We first clarify the precise theoretical foundations behind the notion of diffusion centrality. This allows us to address a minor inconsistency in the model description of Banerjee et al. (2013). We then identify unnatural implicit assumptions in the model of political intermediation proposed by Cruz, Labonne & Querubfn (2017). We introduce two extensions of diffusion centrality, targeting centrality and reachability, which we believe better capture features of contexts with targeted requests. We derive general explicit formulas to compute these new measures.

Suggested Citation

  • Yann Bramoullé & Garance Genicot, 2018. "Diffusion Centrality: Foundations and Extensions," Working Papers halshs-01943760, HAL.
    • Handle: RePEc:hal:wpaper:halshs-01943760
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01943760
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    References listed on IDEAS

    as
    1. Cesi Cruz & Julien Labonne & Pablo Querubín, 2017. "Politician Family Networks and Electoral Outcomes: Evidence from the Philippines," American Economic Review, American Economic Association, vol. 107(10), pages 3006-3037, October.
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    Cited by:

    1. Raúl Duarte & Frederico Finan & Horacio Larreguy & Laura Schechter, 2019. "Brokering Votes With Information Spread Via Social Networks," NBER Working Papers 26241, National Bureau of Economic Research, Inc.
    2. Francis Bloch & Matthew O. Jackson & Pietro Tebaldi, 2023. "Centrality measures in networks," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 61(2), pages 413-453, August.
    3. Rose, Michael E. & Opolot, Daniel C. & Georg, Co-Pierre, 2022. "Discussants," Research Policy, Elsevier, vol. 51(10).
    4. Bayer, Péter & Herings, P. Jean-Jacques & Peeters, Ronald, 2021. "Farsighted manipulation and exploitation in networks," Journal of Economic Theory, Elsevier, vol. 196(C).
    5. Yong Cai, 2022. "Linear Regression with Centrality Measures," Papers 2210.10024, arXiv.org.
    6. King, Maia, 2020. "The probabilities of node-to-node diffusion in fixed networks," SocArXiv dfq8y, Center for Open Science.
    7. Yang Sun & Wei Zhao & Junjie Zhou, 2021. "Structural Interventions in Networks," Papers 2101.12420, arXiv.org, revised Feb 2021.
    8. King, Maia, 2020. "Walk-Independence Probabilities and WIP Centrality: a new heuristic for diffusion probabilities in networks," SocArXiv dfq8y_v1, Center for Open Science.

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    More about this item

    Keywords

    diffusion centrality; Katz-Bonacich centrality; political intermediation; targeting;
    All these keywords.

    JEL classification:

    • O12 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Microeconomic Analyses of Economic Development
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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