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Factors Impacting the Quality of User Answers on Smartphones

arXiv 2306.00627 ↗First posted 1 Jun 2023cs.HC cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 3 of its 25 references that are in the map. First posted on arXiv 1 Jun 2023.

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References · 3

  1. 2020Learning in the Wild with Incremental Skeptical Gaussian Processescited by 12
  2. 2022Lifelong Personal Context Recognitioncited by 2
  3. 2022A Context Model for Personal Data Streamscited by 1

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