Document (#42384)

Author
Wu, Y.
Liu, Y.
Tsai, Y.-H.R.
Yau, S.-T.
Title
Investigating the role of eye movements and physiological signals in search satisfaction prediction using geometric analysis
Source
Journal of the Association for Information Science and Technology. 70(2019) no.9, S.981-999
Year
2019
Abstract
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.
Content
Vgl.: https://onlinelibrary.wiley.com/doi/10.1002/asi.24240.
Footnote
Beitrag in einem 'Special issue on neuro-information science'.
Theme
Benutzerstudien

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