SAMBAVis: Design Study of a Visual Analytics Tool for the Music Industry Powered by YouTube Comments

Abstract

Data from comments on social media platforms offer valuable information about trends and market changes. Aiming at the music industry, we propose SAMBAVis: a visual analytics tool to handle user-generated content from comments left on YouTube music videos. SAMBAVis displays main key performance indexes, video lifecycle, and engagement with comments. It also performs sentiment analysis and extracts the main keywords from the comments, expanding YouTube capabilities. In this paper, we contribute with a design study, explaining the development of SAMBAVis and the rationale of our design. We present a usage scenario and reflect on our methods and results when creating a visualization tool for experts in the music business.