检查会话系统的用户评论：Alexa技能的案例研究
Examining user reviews of conversational systems: a case study of Alexa skills
摘要：
会话系统使用口头语言与用户交互。虽然对话系统，如亚马逊Alexa，正在变得越来越普遍，并提供有趣的功能，但人们对这些系统的用户面临的问题知之甚少。在本文中，我们研究了2,800多个Alexa技能的用户评论，以了解评论的特点和其中提出的问题。我们的研究结果表明，大多数技能收到不到50个评论。我们使用开放编码对用户评论进行了定性研究，发现了用户评论中的16种问题。与内容相关的问题，与在线服务和设备的集成，错误和回归是用户提出的主要问题。我们的研究结果还表明，与更传统的移动应用程序相比，用户投诉的数量和类型存在差异。我们讨论了我们的研究结果对从业人员和研究人员的影响。
英文摘要：
Conversational systems use spoken language to interact with their users. Although conversational systems, such as Amazon Alexa, are becoming common and afford interesting functionalities, there is little known about the issues users of these systems face. In this paper, we study user reviews of more than 2,800 Alexa skills to understand the characteristics of the reviews and issues that are raised in them. Our results suggest that most skills receive less than 50 reviews. Our qualitative study of user reviews using open coding resulted in identifying 16 types of issues in the user reviews. Issues related to the content, integration with online services and devices, error, and regression are top issues raised by the users. Our results also indicate differences in volume and types of complaints by users when compared with more traditional mobile applications. We discuss the implication of our results for practitioners and researchers.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
