Exceptional Collaboration Patterns in Music Genre Networks - Oliveira, Gabriel P.; Moro, Mirella M. (Anais do Brazilian Workshop on Social Network Analysis and Mining (BraSNAM), 2023)
Music is one of the world’s most important cultural forms, and also one of the most dynamic. Such a dynamic nature can directly influence artists’ careers and reflect their success. In this work, we combine social networks and data mining techniques to analyze musical success from a genre-oriented perspective. Our goal is to mine exceptional collaboration patterns in success-based genre networks where the success deviates from the average. We conduct our analyses for global and eight regional markets, and the results show that each market has specific patterns of genre connections in which success is above average. Hence, our findings serve as a first step in developing strategies to promote future song releases across the world.