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Storm crowds: Evidence from Zooniverse on crowd contribution design
Institution:1. Department of Strategy and Innovation, Copenhagen Business School, Denmark;2. École Polytechnique Fédérale de Lausanne, Switzerland;1. Cambridge Mathematics Placements Programme, Faculty of Mathematics, University of Cambridge, Wilberforce Road, Cambridge, CB3 0WA, UK;2. Cato Institute, Washington DC, USA;3. Department of Economics, University of Buckingham, Hunter Street, Buckingham, MK18 1EG, UK;1. College of Business, Alfaisal University, Riyadh, Saudi Arabia;2. College of Business Administration, University of Sharjah, Sharjah, United Arab Emirates;1. Georgia Institute of Technology, School of City and Regional Planning, 245 Fourth Street, Atlanta, GA 30313, United States;2. University of Oregon, Lundquist College of Business, 1208 University Street, Eugene, OR 97403, United States;1. Henley Business School, University of Reading, United Kingdom;2. Imperial College, University of London, United Kingdom;3. Department of Economics, Society and Politics, Carlo Bo University, Urbino, United Kingdom
Abstract:What is the impact of platform design on crowdsourcing contributions? The proliferation of platforms with distributed content production, such as Wikipedia, Zooniverse, and others, has led to scholarly interest in understanding why individuals contribute to them. One stream of research has investigated contributor motivations, while another growing stream, scattered across several disciplines, has explored the effect of platform design on contributions. One important design element is the extent to which incomplete, or partial, contributions are possible - a concept we refer to in this paper as “tolerance to incompleteness.” We explore the relationship between this design element and crowds’ willingness to contribute in the context of Zooniverse, the world’s largest citizen science platform. Our quasi-experimental empirical approach exploits a format change that decreased tolerance to incompleteness in one Zooniverse project. The results of a difference-in-differences estimation show that after the format change, editors contributed fewer total edits, but more complete edits than predicted in the absence of a change. Users also spent less time contributing to the project post-change. Moreover, we find a trade-off between the quantity and quality of complete edits, with the quality of complete edits lower post-change. Our findings have implications for the design of a growing number of crowdsourcing platforms that involve simple, independent, and well-structured tasks.
Keywords:Citizen science  Crowdsourcing  Difference-in-differences  Natural experiment  Zooniverse
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