Getting the Most from Eye-Tracking: User-Interaction Based Reading Region Estimation Dataset and Models
Ruoyan Kong, Ruixuan Sun, Charles Chuankai Zhang, Chen Chen, Sneha Patri, Gayathri Gajjela, Joseph A. Konstan · 2023
A single digital newsletter usually contains many messages (regions). Users’ reading time spent on, and read level (skip/skim/read-in-detail) of each message is important for platforms to understand their users’ interests, personalize their contents, and make recommendations. Based on accurate but expensive-to-collect eyetracker-recorded data, we built models that predict per-region reading time based on easy-to-collect Javascript browser tracking data.