Which algorithmic approach is MOST widely used by major music streaming services (like Spotify) to create personalized music recommendations?

Test your knowledge about how music streaming services personalize your listening experience! Behind those playlists that seem to know your taste better than your friends do, there's sophisticated technology at work. This poll explores the recommendation algorithms that shape our music discovery and listening habits in the digital age. See if you can identify which approach truly powers today's most effective music recommendation systems.

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Pure demographic matching (recommendations based solely on age, location, and gender)
Collaborative filtering (analyzing user behavior patterns and finding similarities between users' listening habits)
Random selection with genre filters (completely random songs within your preferred genres)
Artist-paid promotion algorithms (artists/labels pay for placement in recommendation systems)