2025/03/12 by Bush, Raquel Ana Magalhães
#05C75 (Secondary) #05C82 #91D30 (Primary) 05C90 #FOS: Computer and information sciences #G.2.2 #H.2.8 #I.5.3 #Social and Information Networks (cs.SI)
paper · doi:10.48550/arxiv.2503.09526
This paper examines the small-world properties of a Spotify artist feature collaboration network, focusing on clustering and diameter. We analyze the giant component and subgraphs based on genres, country-specific charts, and detected communities to assess their small-world characteristics. Results indicate that the network is scale-free and follows a power-law degree distribution, with highly popular artists serving as central hubs. Louvain community detection reveals distinct collaboration clusters aligned with genre-based and industry-driven connections. These findings offer insights into music recommendation systems and digital collaboration trends, contributing to a broader understanding of artist networks in the digital age.