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A Survey on Task Assignment in Crowdsourcing

Danula Hettiachchi, Vassilis Kostakos, Jorge Gonçalves

2022ACM Computing Surveys68 citationsDOIOpen Access PDF

Abstract

Quality improvement methods are essential to gathering high-quality crowdsourced data, both for research and industry applications. A popular and broadly applicable method is task assignment that dynamically adjusts crowd workflow parameters. In this survey, we review task assignment methods that address: heterogeneous task assignment, question assignment, and plurality problems in crowdsourcing. We discuss and contrast how these methods estimate worker performance, and highlight potential challenges in their implementation. Finally, we discuss future research directions for task assignment methods, and how crowdsourcing platforms and other stakeholders can benefit from them.

Topics & Concepts

CrowdsourcingComputer scienceWorkflowTask (project management)Quality (philosophy)Data scienceWorld Wide WebDatabaseManagementEpistemologyEconomicsPhilosophyMobile Crowdsensing and CrowdsourcingAuction Theory and ApplicationsData Stream Mining Techniques