So far, most research investigating the predictability of human behavior, such as mobility and social interactions, has focused mainly on the exploitation of sensor data. However, sensor data can be difficult to capture the subjective motivations behind the individuals' behavior. Understanding personal context (e.g., where one is and what they are doing) can greatly increase predictability. The main limitation is that human input is often missing or inaccurate. The goal of this paper is to identify factors that influence the quality of responses when users are asked about their current context. We find that two key factors influence the quality of responses: user reaction time and completion time. These factors correlate with various exogenous causes (e.g., situational context, time of day) and endogenous causes (e.g., procrastination attitude, mood). In turn, we study how these two factors impact the quality of responses.

翻译：迄今为止，大多数关于人类行为（如移动性和社交互动）可预测性的研究主要集中于传感器数据的利用。然而，传感器数据难以捕捉个体行为背后的主观动机。理解个人情境（例如，用户所在位置及当前活动）可以显著提高可预测性。其主要局限性在于人类输入往往缺失或不准确。本文旨在探究当用户被问及当前情境时，影响其回答质量的因素。我们发现，两个关键因素影响回答质量：用户反应时间和完成时间。这些因素与各种外部原因（例如，情境上下文、时间点）和内部原因（例如，拖延态度、情绪）相关。进而，我们研究了这两个因素如何影响回答质量。