This project aims to analyze music playlist data to explore the "hidden associations" between different artists. In this study, each user's playlist or listening record is treated as a "Transaction," while the artists are treated as "Items." By utilizing association rule algorithms (Apriori and Eclat), this research seeks to answer the following questions: 1.The "Genre Anchor" Query: Do fans of modern alternative icons like Coldplay exhibit a statistically significant probability of also following The Killers? 2.The Overlap Mapping: Which artist clusters exhibit the highest degree of fanbase overlap, and do these clusters transcend traditional genre boundaries (e.g., Grunge vs. Metal)? 3.Algorithmic Discovery: How does the Apriori algorithm effectively uncover "hidden bridges" between artists—such as the link between Muse and Radiohead—that simple popularity charts might overlook?