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Modelling Cognitive Bias in Crowdsourcing Systems
Affiliation:1. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210093, China;2. School of Computer Engineering, Nanyang Technological University, Blk N4-02c-110, Nanyang Avenue 639798, Singapore;1. School of Computer Science and Engineering, Central South University, Hunan 410075, PR China;2. School of Computer and Information Engineering, Shanghai Polytechnic University, Shanghai 201209, PR China
Abstract:Crowdsourcing is the process of obtaining input or enlisting the services of a crowd of people with the aim of finding the best solution to a proposed problem. The method with which the collected input is aggregated affects the outcome of the crowdsourcing process. In this paper, we introduce a modelling framework through which we compare several aggregation methods for crowdsourcing systems. The work reveals a surprising result where confidence-related approaches lack in performance when compared to other approaches such as simple plurality voting or approaches which consider respondent competence. This inadequacy stems from a psychological phenomenon brought forth by David Dunning and Justin Kruger related to people’s bias in assessing their own cognitive abilities.
Keywords:Crowdsourcing  Aggregation  Modelling  Cognitive bias  Dunning-Kruger
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