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Hinge’s algorithm, which Mc Leod says is being redesigned, uses two types of filtering to match users who are likely to like each other.One filter uses the same logic as Amazon’s recommendation engine: The same way that Amazon suggests that you buy books that have been purchased by customers’ with a similar purchase history, Hinge shows you the profiles of singles who have been “liked” by users who swipe right on the same profiles as you. If the Hinge algorithm notices that you like people with certain characteristics, it shows you more people with those characteristics.
It’s a strange fact of modern love that some people met their spouse when he had acne and braces while others met their spouse on a date after work.
In fact, many online dating services facilitate assortative matching.
It’s a feature of their matching algorithms, which match people of equal desirability.
This dynamic interested Lucy Hunt, a researcher at the University of Texas at Austin, who decided to investigate “how time might affect how similarly attractive couple members are to one another.” Working with two psychologists, Hunt looked at 167 couples who participated in a long-term study at Northwestern.
They asked each couple how long they’d known each other before they started dating, and they recruited people to watch videotapes of the couples and rate each individual’s physical attractiveness.