Cost-Optimal Validation Mechanisms and Cheat-Detection for Crowdsourcing Platforms

Crowd sourcing is becoming more and more important for commercial purposes. With the growth of crowd sourcing platforms like MTurk or Micro workers, 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 validate the submitted work. Both approaches are evaluated with regard to their detection quality, their costs and their applicability to different types of typical crowd sourcing tasks.