Stylistic Features for Affect-Based Movie Recommendations

In recent years, studies have estimated affective movie content computationally with stylistic features, yet knowledge of the perceptual relation between style and affect remains scarce. Such knowledge would be useful in affect-based movie recommendation systems. To this end, a user study was conducted in which seventy-three participants with varying levels of film expertise rated movie clips according to 13 stylistic features in three modalities (visual, aural and temporal) as well as perceived and felt affect in three dimensions (hedonic tone, energetic arousal and tense arousal). Style-based linear regression models were then constructed for each affect dimension. Visual features contributed the most to hedonic tone and tense arousal, and temporal features to energetic arousal. Also, perceived affect showed greater inter-rater agreement and better modeling performance than felt affect. The results indicate that the influence of specific stylistic features on affect varies by dimension and by whether the affect is perceived or felt.