The dataset captures five years of global music collaborations by processing the Top 200 Global Weekly Spotify Charts from January 1, 2020, to December 31, 2024. From these rankings, we identified 4,390 unique songs and 1,724 unique artists, of which 1,772 songs involved collaborations and 1,315 artists engaged in at least one collaboration. In addition to identifying songs and artists, we collected weekly information on each song’s position in the chart and the corresponding global streaming counts. This information, recorded systematically on a weekly basis, is available in the file named top200_global_songs_spotify_2020_2024.csv.

Based on this dataset, we constructed a bipartite network of songs and artists, which was then projected onto the artist layer to obtain collaboration ties. In the giant connected component of this projection, the network comprises 906 artists and 2,281 collaboration edges. For these artists, we further enriched the data with sociocultural metadata obtained primarily from Wikidata and YouTube. This enrichment provides information such as country of origin, age, educational background, gender, musical genres, and languages used across their songs. The inclusion of this metadata aims to facilitate the study of potential factors that influence the formation of musical collaborations.