Modeling the Impact of Video Dynamics on User Engagement and Eye Tracking Patterns.

Video content on the internet commands a substantial portion of online activities and holds immense value in driving effective marketing campaigns. The question is, how can we measure the potential of video content to capture user attention and how to improve video effectiveness without techniques that increase cognitive load and result in avoidance and skipping of advertisements. This study investigated how video dynamics represented by dedicated metrics is related to eye-tracking patterns and whether video dynamics can be a predictor of user engagement represented by the number of fixations and the duration of gaze on video content. The results showed that selected metrics can serve as predictors of eye movement patterns and that video dynamics have a real impact on user engagement with the viewed video content. [ABSTRACT FROM AUTHOR]