Optimal Design for Social Learning
Yeon-Koo Che,Johannes Hörner +1 more
TLDR
This paper studies the design of a recommender system for organizing social learning on a product and finds that fully transparent recommendations may become optimal if a (socially-benevolent) designer does not observe the agents’ costs of experimentation.Abstract:
This paper studies the design of a recommender system for organizing social learning on a product. To improve incentives for early experimentation, the optimal design trades off fully transparent social learning by over-recommending a product (or “spamming”) to a fraction of agents in the early phase of the product cycle. Under the optimal scheme, the designer spams very little about a product right after its release but gradually increases the frequency of spamming and stops it altogether when the product is deemed sufficiently unworthy of recommendation. The optimal recommender system involves randomly triggered spamming when recommendations are public—as is often the case for product ratings—and an information “blackout” followed by a burst of spamming when agents can choose when to check in for a recommendation. Fully transparent recommendations may become optimal if a (socially-benevolent) designer does not observe the agents’ costs of experimentation.read more
Citations
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Journal ArticleDOI
Dynamic Bayesian Persuasion with Public News
TL;DR: In this article, the effect of exogenous news in dynamic games of Bayesian persuasion is studied, and it is shown that in equilibrium the action of the receiver may be delayed, even though players are impatient and tests are costless.
Proceedings ArticleDOI
Diversity and Exploration in Social Learning
TL;DR: It is shown that intermediate diversity levels yield significantly higher social utility than the extreme cases of no diversity or full diversity and how the impact of the diversity level changes depending on the time spent searching is quantified.
Dissertation
Essays in Dynamic Games
TL;DR: In this paper, the authors discuss the adoption of forward-looking social learners by Forward-Looking Social Learners (FSLL) in the context of innovation adoption by forward looking social learners.
Journal ArticleDOI
Strategic Experimentation with Random Serial Dictatorship
TL;DR: In this paper, the authors consider matching-mechanism design in an environment in which agents acquire information about their preferences endogenously, and show that the implementation of matching mechanisms changes the equilibrium consequence because it influences agents' beliefs about choice sets.
Posted ContentDOI
Crowd Learning without Herding : A Mechanism Design Approach
TL;DR: In this article, the optimal policy of a central planner regarding when to provide information and how much information to provide is studied, and it is shown that the optimum policy involves a delicate balance of hiding and revealing information.
References
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Posted Content
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Journal ArticleDOI
A Theory of Fads, Fashion, Custom, and Cultural Change as Informational Cascades
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Wendell H. Fleming,H. Mete Soner +1 more
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