In this paper, published in Proceedings of ACM Human-Computer Interaction (CSCW), we examine the changes in motivation factors in crowdsourced policymaking. By drawing on longitudinal data from a crowdsourced law reform, we show that people participated because they wanted to improve the law, learn, and solve problems. When crowdsourcing reached a saturation point, the motivation factors weakened and the crowd disengaged. Learning was the only factor that did not weaken. The participants learned while interacting with others, and the more actively the participants commented, the more likely they stayed engaged. Crowdsourced policymaking should thus be designed to support both epistemic and interactive aspects. While the crowd’s motives were rooted in self-interest, their knowledge perspective showed common-good orientation, implying that rather than being dichotomous, motivation factors move on a continuum. The design of crowdsourced policymaking should support the dynamic nature of the process and the motivation factors driving it.
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