Liking is one of the most important psychological processes associated with the reward system, being involved in affective processing and pleasure/displeasure encoding. Currently, there is no consensus regarding the combination of physiological indicators which best predict liking, especially when applied to dynamic stimuli such as videos. There is a lack of a standard methodology to assess likeability over time and therefore in assessing narrative and semantic aspects of the stimulus. We developed a time-dependent method to evaluate the physiological correlates of likeability for three different thematic categories, namely: adventure (AV), comedy (CM), and nature landscape (LS). Twenty-eight healthy adults with ages ranging from 18 to 35 years (average: 23.85 years) were enrolled in the study. The participants were asked to provide likeability ratings for videos as they watched them, using a response box. Three 60-s videos were presented, one for each category, in randomized order while the participant's physiological data [electroencephalogram (EEG), electrocardiogram (ECG) and eye tracking (ET)] was recorded. The comedy video (CM) presented the smallest minimum accumulated normalized rating (ANR; = 0.013) and the LS video presented the highest maximum ANR ( = 0.039). The LS video presented the longest time for first response ( < 0.001) and the AV video presented the shortest time for maximum response ( = 0.016). The LS video had the highest mean likeability rating with 1.43 ± 2.31 points; and the CM video had the lowest with 0.57 ± 1.77. Multiple linear regression models were created to predict the likeability of each video using the following physiological indicators; AV: power in beta band at C4 and P4 ( = 0.004, adj. = 0.301); CM: alpha power in Fp2 ( = 0.001, adj. = 0.326) and LS: alpha power in P4, F8, and Fp2; beta power in C4 and P4 and pupil size, ( = 0.002, adj. = 0.489). Despite its limitations (e.g., using one 1-min video per category) our findings suggest that there is a considerable difference in the psychophysiological correlates of stimuli with different contextual properties and that the use of time-dependent methods to assess videos should be considered as best practices.