Soowon Kang
KAIST, Daejeon, Korea, Republic of
Mobile experience sampling methods~(ESMs) are widely used to measure users' affective states by randomly sending self-report requests. However, this random probing can interrupt users and adversely influence users' emotional states by inducing disturbance and stress. This work aims to understand how ESMs themselves may compromise the validity of ESM responses and what contextual factors contribute to changes in emotions when users respond to ESMs. Towards this goal, we analyze 2,227 samples of the mobile ESM data collected from 78 participants. Our results show ESM interruptions positively or negatively affected users' emotional states in at least 38\% of ESMs, and the changes in emotions are closely related to the contexts users were in prior to ESMs. Finally, we discuss the implications of using the ESM and possible considerations for mitigating the variability in emotional responses in the context of mobile data collection for affective computing.
https://dl.acm.org/doi/abs/10.1145/3491102.3501944
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)