A Multimodal Computational Aesthetics Analysis of Audio-Visual Features and Audience Reception in BINI's Music Videos

This article analyzes the audiovisual style and fan comments for two eras of BINI music videos. To obtain a computational-aesthetics and multimodal-sentiment approach, both video and audio feature extraction such as brightness, saturation, motion, tempo, and spectral centroid, and natural language emotion and sentiment analysis of YouTube comments were conducted. Pantropiko showed that it contains high valence and collective joy, while Cherry On Top is characterized by more continuity, strong motion energy, and higher tempo, generating admiration and excitement. Fans talk about motion and excitement in ways that match how they perceive the music videos. This shows that the feelings they express in comments reflect their real perceptual experience. The results back up the idea that how much visual or sound intensity something has can change simple enjoyment into a deeper, more intellectual appreciation. Beyond pop-culture analysis, this study also contributes a reproducible workflow linking computational media analysis and emotion modeling, with potential applications for digital adaptive multimedia design, cultural analytics, and educational content development. Overall, this study demonstrates how data-driven aesthetics can both measure and explain how design choices influence collective feeling in digital culture.