How Content Streaming Services Users Make Sense of the Algorithm-Generated Viewing Recommendations

Patrick Watson's SSHRC Funded Research

Do you share a Netflix, Spotify, Hulu, etc. streaming account with your family, friends, or strangers? Do you ever wonder how your account gives you weird recommendations after you share your password with your new boyfriend or girlfriend? If so, we want to talk to you!

Gaming Predictive Subscription Algorithms is a one-year project examining how content streaming services users make sense of the recommendation algorithms these services employ. We’re particularly interested in users who share accounts with people they don’t live with, since these tend to be the scenarios where the recommendation algorithm makes the strangest recommendations. There is a lot of scholarly interest in how people interact with algorithms and other digital agents, but the problem is, most of the time, we don’t know that we are interacting with them.

Algorithms are being used more and more every day to predict what we might do, either collectively or individually, and the services we use and organizations we interact with are being guided by them, but for the most part these remain hidden to us and we don’t know a ton about how they work or how we should feel about them. Recommenders, on the other hand, are algos that we “see” working all the time and interact with more or less directly, so our question is “how do people feel about those interactions?” Knowing more about this will lead us to better understand what impacts algos and digital agents are having on our lives.