28.06.2022 Neuer Preprint: Expertise in Sequential Collaboration

Expertise Determines Frequency and Accuracy of Contributions in Sequential Collaboration

Maren Mayer, Marcel Broß & Daniel W. Heck

Many collaborative online projects such as Wikipedia and OpenStreetMap organize collaboration among their contributors sequentially. In sequential collaboration, one contributor creates an entry which is consecutively encountered by other contributors who then decide whether to adjust or maintain the presented entry. Sequential collaboration yields improved judgments over the course of a sequential chain and results in accurate final estimates. We hypothesize that these benefits emerge since contributors adjust entries according to their expertise, implying that judgments of experts have a larger impact compared to those of novices. In three preregistered studies, we measured and manipulated expertise to investigate whether expertise leads to higher change probabilities and larger improvements in judgment accuracy. Moreover, we tested whether expertise results in an increase in accuracy over the course of a sequential chain. As expected, experts adjusted entries more frequently, made larger improvements, and contributed more to the final estimates of sequential chains. Overall, our findings show that the high accuracy of sequential collaboration is due to an implict weighting of judgments by expertise.

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