Game-Theoretic Design of Optimal Two-Sided Rating Protocols for Service Exchange Dilemma in Crowdsourcing

by   Jianfeng Lu, et al.

Despite the increasing popularity and successful examples of crowdsourcing, its openness overshadows important episodes when elaborate sabotage derailed or severely hindered collective efforts. A service exchange dilemma arises when non-cooperation among self-interested users, and zero social welfare is obtained at myopic equilibrium. Traditional rating protocols are not effective to overcome the inefficiency of the socially undesirable equilibrium due to specific features of crowdsourcing: a large number of anonymous users having asymmetric service requirements, different service capabilities, and dynamically joining/leaving a crowdsourcing platform with imperfect monitoring. In this paper, we develop the first game-theoretic design of the two-sided rating protocol to stimulate cooperation among self-interested users, which consists of a recommended strategy and a rating update rule. The recommended strategy recommends a desirable behavior from three predefined plans according to intrinsic parameters, while the rating update rule involves the update of ratings of both users, and uses differential punishments that punish users with different ratings differently. By quantifying necessary and sufficient conditions for a sustainable social norm, we formulate the problem of designing an optimal two-sided rating protocol that maximizes the social welfare among all sustainable protocols, provide design guidelines for optimal two-sided rating protocols and a low-complexity algorithm to select optimal design parameters in an alternate manner. Finally, illustrative results show the validity and effectiveness of our proposed protocol designed for service exchange dilemma in crowdsourcing.


Rating Protocol Design for Extortion and Cooperation in the Crowdsourcing Contest Dilemma

Crowdsourcing has emerged as a paradigm for leveraging human intelligenc...

Reputation-based Incentive Protocols in Crowdsourcing Applications

Crowdsourcing websites (e.g. Yahoo! Answers, Amazon Mechanical Turk, and...

RewardRating: A Mechanism Design Approach to Improve Rating Systems

Nowadays, rating systems play a crucial role in the attraction of custom...

Bribery in Rating System: A Game-Theoretic Perspective

The rich revenue gained from a mobile application (a.k.a. app) boost app...

Zero-Rating and Net Neutrality: Who Wins, Who Loses?

An objective of network neutrality is that the design of regulations for...

Collaborative Filtering and the Missing at Random Assumption

Rating prediction is an important application, and a popular research to...

Designing Approximately Optimal Search on Matching Platforms

We study the design of a decentralized two-sided matching market in whic...

Please sign up or login with your details

Forgot password? Click here to reset