对GitHub上Bot评论反应的探索性研究

Juan Carlos Farah, Basile Spaenlehauer, Xinyang Lu, Sandy Ingram, D. Gillet
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引用次数: 6

摘要

机器人广泛用于支持软件开发,使得GitHub等社交编码平台成为研究人机交互的特别丰富的数据来源。软件开发机器人用于自动化重复任务,通过在这些平台上可用的各种讨论界面上发布的评论与人类同行进行交互。GitHub支持的一种交互类型包括使用预定义的表情符号对评论做出反应。为了调查用户对机器人评论的反应,我们进行了一项观察性研究,包括5400万条GitHub评论,特别关注那些引起笑声反应的评论。我们的分析结果表明,在人类和机器人的评论中,有些反应类型并不是均匀分布的,机器人的设计和目的会影响它收到的反应类型。此外,虽然笑的反应不是专门用来表达笑,但当机器人的行为出乎意料时,它可以用来传达幽默。这些见解可以指导机器人的设计方式,并帮助开发人员使它们具备识别和从意外情况中恢复的能力。反过来,机器人可以更好地支持使用社交编码平台的团队的沟通、协作和生产力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Exploratory Study of Reactions to Bot Comments on GitHub
The widespread use of bots to support software development makes social coding platforms such as GitHub a particularly rich source of data for the study of human-bot interaction. Software development bots are used to automate repetitive tasks, interacting with their human counterparts via comments posted on the various discussion interfaces available on such platforms. One type of interaction supported by GitHub involves reacting to comments using predefined emoji. To investigate how users react to bot comments, we conducted an observational study comprising 54 million GitHub comments, with a particular focus on comments that elicited the laugh reaction. The results from our analysis suggest that some reaction types are not equally distributed across human and bot comments and that a bot's design and purpose influence the types of reactions it receives. Furthermore, while the laugh reaction is not exclusively used to express laughter, it can be used to convey humor when a bot behaves unexpectedly. These insights could inform the way bots are designed and help developers equip them with the ability to recognize and recover from unanticipated situations. In turn, bots could better support the communication, collaboration, and productivity of teams using social coding platforms.
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