Hinge and Machine Learning: The makings of a perfect match

Hinge and Machine Learning: The makings of a perfect match

“There are plenty of fish in the sea…” To a modern dater, this old adage about finding love seems almost eerie in its prescience of the emergence of online dating. With the rapid rise of Match, Tinder, Bumble, and more, it is unsurprising that recent estimates suggest that the proportion of the U.S. adult population using dating apps or websites has grown from 3% in 2008 to over 15% today .

One such app, Hinge, launched in 2012. Its basic premise is to show a user some number of profiles for other suitable singles. If a Hinge user spots someone of interest while browsing, he or she can reply to a particular element of that person’s profile to start a conversation – much in the same way a user on Facebook can “like” and comment on another user’s newsfeed posts.

This model is not a massive departure from the formulas used by older competitors like OkCupid and Tinder. However, Hinge differentiates itself with the pitch that it is the best of all the platforms in creating online matches that translate to quality relationships offline.Continue reading