Analyzing Audience Engagement in Static Versus Dynamic Media Content Using Eye-Tracking and Instagram Metrics Through the Lens of TPB and CLT

Understanding audience engagement in media content is essential, as neuroscientific techniques provide insights into psychological and cognitive responses. This study conducts a quantitative comparative analysis of audience engagement with static designs and dynamic audiovisual content using Realeye.io, a webcam-based eye-tracking tool. Fifteen participants (60% female, 40% male) were analyzed, revealing that dynamic content outperforms static designs. The number of fixations was higher for dynamic media (M = 155.2, SD = 18.00) than for static (M = 27.33, SD = 3.79), with longer fixation duration (M = 43.85s, SD = 5.72) compared to static (M = 25.4s, SD = 2.69), confirmed by the Wilcoxon signed-rank test (Z = -3.297, P < 0.001). The study also examines Instagram engagement metrics for 30 movie posters and trailers. Results show that trailers receive more likes (M = 124,945, SD = 187,019) than posters (M = 71,597, SD = 174,257), except for Mission Impossible, where the poster (900k likes) outperformed the trailer (250k). Findings were interpreted using the Theory of Planned Behavior and Cognitive Load Theory (CLT), emphasizing behavioral and cognitive mechanisms. Limitations include a small sample size, reliance on a single eye-tracking tool, and Instagram as the sole data source. Ethical approval was obtained from Eastern Mediterranean University, and all procedures involving human participants complied with relevant ethical standards