Predicting musician success from early career collaboration structures

Abstract This work investigates whether early-career collaboration structures among musicians can predict long-term artistic success. Using MusicBrainz and Spotify data, we construct a large-scale collaboration network and model the generative processes underlying tie formation using Exponential Random Graph Models (ERGMs). We show that structural tendencies such as triadic closure, homophily, and productivity-driven exposure shape early collaboration, while weak ties are underrepresented relative to structural expectations. Using these insights, we engineer interpretable features and learned graph embeddings to predict long-term success, measured by Spotify follower count. Our findings demonstrate that early-network connectivity—particularly weak ties, cross-community bridging, and deviations from expected structural patterns—adds predictive signal beyond metadata baselines. Similar content being viewed by others Funding This research received no external funding. Author information Authors and Affiliations Corresponding author Ethics declarations Conflict of interest The authors declare no conflict of interest. Additional information Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Rights and permissions Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. About this article Cite this article Woodburn, K., Frey, C., Petterson, C. et al. Predicting musician success from early career collaboration structures. Appl Netw Sci (2026). https://doi.org/10.1007/s41109-026-00823-1 Received: Accepted: Published: DOI: https://doi.org/10.1007/s41109-026-00823-1