The Science Behind Dating Algorithms
I spent three months in 2022 reporting on dating algorithms, interviewing engineers at Hinge and researchers at Stanford. What I learned changed how I use these apps.
Elo and Desirability Scores
Tinder popularized (then claimed to move beyond) the Elo system from chess. Basic concept: right-swipes from highly-desired users boost your score more. Left-swipes lower it. Your score determines who sees you and in what order.
Most apps have evolved past pure Elo, but reciprocal desirability scoring remains embedded.
Collaborative Filtering
Netflix-style recommendations applied to people. The algorithm notices that users with your swiping patterns tend to like certain profiles, then surfaces those for you -- even if they're outside your stated preferences. This explains those seemingly random suggestions that turn out surprisingly good.
Machine Learning Goes Deeper
Dwell time: 4 seconds then left-swipe tells the algorithm less than 15 seconds then left-swipe.
Messaging behavior: Who you message first, response speed, conversation length, whether numbers get exchanged. Weighted more heavily than swipes.
Photo engagement: Some apps identify which profile elements attract your attention and surface more of those patterns.
The Gale-Shapley Algorithm
Hinge uses this Nobel Prize-winning model to find "stable matches" -- not just who you'd like, but who'd like you back. The Most Compatible suggestion consistently produces higher match rates than regular browsing because it optimizes for mutual interest.
Personality-Based Matching
eHarmony (32 dimensions), Parship (136 rules), EliteSingles -- questionnaire-based matching. A 2012 study found these predict relationship satisfaction once established, though they're weaker at predicting initial attraction.
Working With the System
Complete your profile fully -- more data means better matches. Be consistent in your behavior. Engage with matches (algorithms reward active users). Use the app regularly but moderately. Update your profile periodically for algorithmic boosts.
The algorithms are sophisticated tools, not magic. Feed them honest signals about who you actually want to meet, and they get dramatically better at their job.
