论文标题
在智能日常应用中引起用户报告的问题的方法和分析
A Method and Analysis to Elicit User-reported Problems in Intelligent Everyday Applications
论文作者
论文摘要
智能系统的复杂性质激发了在互动过程中支持用户的工作，例如通过解释。但是，到目前为止，关于用户在日常情况下应用此类系统时面临的特定问题，几乎没有经验证据。本文贡献了一种新颖的方法和分析，以调查用户报告的问题：我们分析了45,448个对Google Play商店（Facebook，Netflix，Google Maps和Google Assistant）在Google Play商店（Facebook，Netflix，Google Map和Google Assistant）上进行的评论，并通过情感分析和主题建模来揭示互动过程中的问题，这些问题可以归因于应用程序的Algorithmic决策。我们通过后续在线调查（n = 286），用用户的应对和支持策略丰富了这些数据。特别是，我们发现了与内容，算法，用户选择和反馈有关的问题和策略。我们讨论了设计用户支持的相应含义，突出了用户控制的重要性和输出的解释，而不是流程。
The complex nature of intelligent systems motivates work on supporting users during interaction, for example through explanations. However, as of yet, there is little empirical evidence in regard to specific problems users face when applying such systems in everyday situations. This paper contributes a novel method and analysis to investigate such problems as reported by users: We analysed 45,448 reviews of four apps on the Google Play Store (Facebook, Netflix, Google Maps and Google Assistant) with sentiment analysis and topic modelling to reveal problems during interaction that can be attributed to the apps' algorithmic decision-making. We enriched this data with users' coping and support strategies through a follow-up online survey (N=286). In particular, we found problems and strategies related to content, algorithm, user choice, and feedback. We discuss corresponding implications for designing user support, highlighting the importance of user control and explanations of output, rather than processes.
