Many open collaboration platforms (e.g., Wikipedia) have recently utilized automated algorithmic agents, called Bots, to solve the issue of stagnating user participation. However, understanding of how such a bot agent affects user activities in open collaboration is limited. In this study, we examine (i) whether bot intervention affects user participation and (ii) whether the impact of bot intervention could vary by characteristics of open collaboration works. We pursue our research goals by utilizing a rich dataset from between 2005 and 2017 from an online open collaboration platform. The platform has recently utilized two types of unique bots that interact with human users in open collaboration. By employing difference-in-differences approach, we show that bot intervention in open collaboration leads to unintended consequences as it significantly demotivates user participation. We further show that the negative effect of bot intervention is alleviated if more active users are engaged or if covered topics have a higher concentration in a collaboration work. This provides directions for businesses to resolve the unintended demotivation problem in utilizing bot agents.

许多开放协作平台（例如，维基百科）最近使用了自动化算法代理，称为机器人，解决用户参与停滞的问题。然而，对这种机器人代理如何影响开放协作中的用户活动的理解是有限的。在本研究中，我们检查 (i) 机器人干预是否影响用户参与以及 (ii) 机器人干预的影响是否会因开放协作作品的特征而异。我们通过使用来自在线开放协作平台的 2005 年至 2017 年的丰富数据集来实现我们的研究目标。该平台最近使用了两种独特的机器人，它们在开放式协作中与人类用户进行交互。通过采用差异中的差异方法，我们表明开放协作中的机器人干预会导致意想不到的后果，因为它显着降低了用户参与的积极性。我们进一步表明，如果有更多活跃的用户参与或如果涵盖的主题在协作工作中更加集中，则机器人干预的负面影响会得到缓解。这为企业解决在利用机器人代理时意外的消极怠工问题提供了指导。