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，大多数研究人类行为可预测性（如移动性和社交互动）的工作主要集中在传感器数据的利用上。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，用户所处位置及其正在从事的活动）能够显著提高可预测性。其主要限制在于，人类输入常常缺失或不准确。本文旨在识别影响用户被询问当前情境时回答质量的因素。我们发现，两个关键因素会显著影响回答质量：用户反应时间和完成时间。这些因素与外源性因素（例如，情境背景、一天中的时间）和内源性因素（例如，拖延倾向、情绪）相关。进而，我们研究了这两个因素对回答质量的影响机制。