Design & Application of Crowdsourcing Studies - Lessons Learned and Best practices

Crowdsourcing offers the possibility to gain access to a huge number of potential participants for research studies, e.g. QoE studies. While realizing and conducting such studies on crowdsourcing platforms, new challenges arise which differ from known challenges of studies in laboratory environments. This lecture gives a short introduction to crowdsourcing, especially to microtasking and a brief overview of commonly used platforms like Amazon Mechanical Turk and Microworkers. Further, the lecture discusses how to design and realize crowdsourcing studies focussing on factors which affect the quality of the output of the conducted studies.

About the speaker

Kathrin Borchert Kathrin Borchert
University of Würzburg

Kathrin Borchert is a PhD student at the Chair of Communication Networks at the University of Würzburg since late 2014. Starting with her Master’s Thesis on the integration of recommendation systems in crowdsourcing platforms, she continued her research in this area focusing on optimization mechanisms for crowdsourcing workflows and task design. Recently, she investigates the quality of business applications perceived by employees as an enterprise crowdsourcing use-case.