TY - JOUR TI - Investigating the role of eye movements and physiological signals in search satisfaction prediction using geometric analysis AU - Wu, Yingying AU - Liu, Yiqun AU - Tsai, Yen-Hsi Richard AU - Yau, Shing-Tung T2 - Journal of the Association for Information Science and Technology AB - Two general challenges faced by data analysis are the existence of noise and the extraction of meaningful information from collected data. In this study, we used a multiscale framework to reduce the effects caused by noise and to extract explainable geometric properties to characterize finite metric spaces. We conducted lab experiments that integrated the use of eye-tracking, electrodermal activity (EDA), and user logs to explore users' information-seeking behaviors on search engine result pages (SERPs). Experimental results of 1,590 search queries showed that the proposed strategies effectively predicted query-level user satisfaction using EDA and eye-tracking data. The bootstrap analysis showed that combining EDA and eye-tracking data with user behavior data extracted from user logs led to a significantly better linear model fit than using user behavior data alone. Furthermore, cross-user and cross-task validations showed that our methods can be generalized to different search engine users performing different preassigned tasks. DA - 2019/// PY - 2019 DO - 10.1002/asi.24240 DP - Wiley Online Library VL - 70 IS - 9 SP - 981 EP - 999 LA - en SN - 2330-1643 UR - https://asistdl.onlinelibrary.wiley.com/doi/abs/10.1002/asi.24240 Y2 - 2019/10/23/16:43:02 ER -