Spotify Recommendation Algorithm Research Zine
A research-driven editorial zine exploring how Spotify recommendation systems shape listening behavior, discovery, and personalization.
Overview
This project investigates Spotify's recommendation ecosystem through a visual research format that combines technical analysis with editorial storytelling. The goal was to unpack how recommendation signals, listening history, and platform design patterns influence what users discover and how their habits evolve over time.
My Role
I designed and authored the full research zine, including literature review synthesis, system breakdowns, narrative structure, and visual direction. I translated technical recommendation-system concepts into a readable magazine format intended for both technical and non-technical audiences.
Spotify Recommendation Algorithm
Zine Reader
Spotify Recommendation Algorithm
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Outcome
The final deliverable is a multi-page interactive zine that presents recommendation-system mechanics, observed user impacts, and key takeaways in a format that is easier to engage with than a conventional report. It demonstrates my ability to merge research, critical analysis, and communication design into a single product experience.
Next Project
DIY CDJ with DAW Integration