Accelerating Creator Audience Building through Centralized Exploration

Abstract

On Spotify, multiple recommender systems enable personalized user experiences across a wide range of product features. These systems are owned by different teams and serve different goals, but all of these systems need to explore and learn about new content as it appears on the platform. In this work, we describe ongoing efforts at Spotify to develop an efficient solution to this problem, by centralizing content exploration and providing signals to existing, decentralized recommendation systems (a.k.a. exploitation systems). We take a creator-centric perspective, and argue that this approach can dramatically reduce the time it takes for new content to reach its full potential.

Related

November 2024 | SIAM Journal on Mathematics of Data Science

Topological Fingerprints for Audio Identification

Wojciech Reise, Ximena Fernández, Maria Dominguez, Heather A. Harrington, Mariano Beguerisse-Díaz

October 2024 | CIKM

PODTILE: Facilitating Podcast Episode Browsing with Auto-generated Chapters

A. Ghazimatin, E. Garmash, G. Penha, K. Sheets, M. Achenbach, O. Semerci, R. Galvez, M. Tannenberg, S. Mantravadi, D. Narayanan, O. Kalaydzhyan, D. Cole, B. Carterette, A. Clifton, P. N. Bennett, C. Hauff, M. Lalmas-Roelleke

October 2024 | Journal of Online Trust & Safety

Algorithmic Impact Assessments at Scale: Practitioners’ Challenges and Needs

Amar Ashar, Karim Ginena, Maria Cipollone, Renata Barreto, Henriette Cramer