Optimal influence design in networks

Daeyoung Jeong and Euncheol Shin

Journal of Economic Theory, 2024, vol. 220, issue C

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.

Keywords: Davis–Kahan sin⁡Θ theorem; Singular value decomposition; Social learning; Social networks; Wedin sin⁡Θ theorem (search for similar items in EconPapers)
JEL-codes: D83 D85 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0022053124000838
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jetheo:v:220:y:2024:i:c:s0022053124000838

DOI: 10.1016/j.jet.2024.105877

Access Statistics for this article

Journal of Economic Theory is currently edited by A. Lizzeri and K. Shell

More articles in Journal of Economic Theory from Elsevier
Bibliographic data for series maintained by Catherine Liu ().