Abstract
Human-computer systems are increasingly applied to data reduction problems; citizen science platforms (e.g. the Zooniverse) are one type of such a system. These platforms function as social machines, combining volunteer efforts with automated processes to enable distributed data analysis. The rapid growth of this approach is increasing the need to understand how we can improve volunteer interaction and engagement. Here, we utilize the most comprehensive collection of online citizen science data gathered to date to examine multiple variables across 63 Zooniverse projects. Our analyses reveal how subtle design changes can influence many facets of volunteer interaction, generating insights that have implications for the design and study of citizen science projects, and future research.
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