Social comparison-based features are widely used in social computing apps. However, most existing apps are not grounded in social comparison theories and do not consider individual differences in social comparison preferences and reactions. This paper is among the first to automatically personalize social comparison targets. In the context of an m-health app for physical activity, we use artificial intelligence (AI) techniques of multi-armed bandits. Results from our user study (n=53) indicate that there is some evidence that motivation can be increased using the AI-based personalization of social comparison. The detected effects achieved small-to-moderate effect sizes, illustrating the real-world implications of the intervention for enhancing motivation and physical activity. In addition to design implications for social comparison features in social apps, this paper identified the personalization paradox, the conflict between user modeling and adaptation, as a key design challenge of personalized applications for behavior change. Additionally, we propose research directions to mitigate this Personalization Paradox.

翻译：在社会计算应用中广泛使用基于社会比较的特征。然而,大多数现有应用并不基于社会比较理论,也不考虑社会比较偏好和反应方面的个人差异。本文是第一个将社会比较目标自动个人化的文件。在体育活动的移动健康应用中,我们使用多臂强盗的人工智能技术。我们的用户研究结果(n=53)表明,一些证据表明,利用基于AI的个体化社会比较可以提高动力。检测到的效果达到了小至中位效应大小,说明了干预对增强动力和体力活动的实际影响。除了设计社会比较特征的影响外,本文还确定了个人化悖论、用户建模和适应之间的冲突,作为个人化应用改变行为的关键设计挑战。此外,我们提出了减少个人化影响的研究方向。