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Simulation of Consensus Based Approaches to Mitigate the Challenges in Crowdsourcing

Crowdsourcing is an emerging area and has evolved as a powerful practice to leverage the collective intelligence of the crowd. It has been applied in various domains ranging from creative resolution of a problem to improving the business process using several platforms such as CrowdFlower, Freelancer and Amazon Mechanical Turk. Crowd is a creative workforce that has niche abilities to solve complex business challenges across various domains. It can be seen as an alternate workforce by participating in all phases of software development life cycle. However the common problem seen in crowdsourcing is the quality of the work performed by the crowd mostly due to the anonymity of the crowd member. In this work, we evaluated consensus based approach to assess the quality of the work done by the crowd through a simulation of crowd behavior. We also investigated the performance of these techniques for evaluating crowd members.