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Optimal influence design in networks

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  • Jeong, Daeyoung
  • Shin, Euncheol

Abstract

We examine an influence designer's optimal intervention in the presence of social learning in a network. Before learning begins, the designer alters initial opinions of agents within the network to shift their ultimate opinions to be as close as possible to the target opinions. By decomposing the influence matrix, which summarizes the learning structure, we transform the designer's problem into one with an orthogonal basis. This transformation allows us to characterize optimal interventions under complete information. We also demonstrate that even in cases where the designer has incomplete information about the network structure, the designer can still design an asymptotically optimal intervention in a large network. Finally, we provide examples and extensions, including repeated social learning and competition.

Suggested Citation

  • Jeong, Daeyoung & Shin, Euncheol, 2024. "Optimal influence design in networks," Journal of Economic Theory, Elsevier, vol. 220(C).
    • Handle: RePEc:eee:jetheo:v:220:y:2024:i:c:s0022053124000838
    DOI: 10.1016/j.jet.2024.105877
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    Cited by:

    1. Daeyoung Jeong & Tongseok Lim & Euncheol Shin, 2024. "Robust Intervention in Networks," Papers 2501.00235, arXiv.org, revised Feb 2025.
    2. Benjamin Golub, 2025. "Eigenvalues in microeconomics," Papers 2502.12309, arXiv.org.

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    More about this item

    Keywords

    Davis–Kahan sin⁡Θ theorem; Singular value decomposition; Social learning; Social networks; Wedin sin⁡Θ theorem;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation

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