Perceptions and Truth: A Mechanism Design Approach to Crowd-Sourcing Reputation
Parinaz Naghizadeh, Mingyan Liu

TL;DR
This paper explores how to design incentive mechanisms in distributed multi-user systems to accurately assess reputations despite users' private information and strategic behavior, using a game-theoretic approach.
Contribution
It introduces utility models capturing strategic user behavior and develops mechanisms that incentivize truthful participation, achieving optimal or near-optimal reputation assessments.
Findings
Mechanisms can incentivize truthful reporting in reputation systems.
Punish-reward strategies improve system performance even when optimal solutions are unattainable.
Users are motivated to participate and share information through designed incentives.
Abstract
We consider a distributed multi-user system where individual entities possess observations or perceptions of one another, while the truth is only known to themselves, and they might have an interest in withholding or distorting the truth. We ask the question whether it is possible for the system as a whole to arrive at the correct perceptions or assessment of all users, referred to as their reputation, by encouraging or incentivizing the users to participate in a collective effort without violating private information and self-interest. Two specific applications, online shopping and network reputation, are provided to motivate our study and interpret the results. In this paper we investigate this problem using a mechanism design theoretic approach. We introduce a number of utility models representing users' strategic behavior, each consisting of one or both of a truth element and an…
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Taxonomy
TopicsAuction Theory and Applications · Game Theory and Applications · Game Theory and Voting Systems
