Cheat-Detection Mechanisms for Crowdsourcing

Crowdsourcing is becoming more and more important for commercial purposes. With the growth of crowdsourcing platforms like MTurk, Microworkers or Inno- centive, a huge work force and a large knowledge base can be easily accessed and utilized. But due to the anonymity of the workers, they are encouraged to cheat the employers in order to maximize their income. Thus, this paper presents two crowd- based approaches to detect cheating workers. Both approaches are evaluated with regard to their detection quality, their costs and their applicability to different types of typical crowdsourcing tasks.