How the other swiping apps and algorithms are different (even though Tinder’s is the best)
There are a lot of conspiracy theories about Tinder “crippling” the standard, free version of the app and making it basically unusable unless you pay for a premium account or add-ons, like extra Super Likes and Boosts (the option to serve your profile to an increased number of people in your area for a limited amount of time). There is also, unfortunately, a subreddit specifically for discussing the challenges of Tinder, in which guys write things like, “The trick: for every girl you like, reject 5 girls.” And, “I installed tinder 6 days ago, ZERO matches and trust me, im not ugly, im not fucking brad pitt but what the fuck?? anyways i installed a new account with a random guy from instagram, muscular and beautiful, still ZERO matches …”
I can’t speak to whether Tinder is actually stacking the deck against these men, but I will point out that some reports put the ratio at 62-38 men to women on the app. And that ratio changes based on geography – your match rate depends a lot on your local population dynamics.
Hinge – the “relationship app” with profiles more robust than Tinder’s but far less detailed than something like OkCupid or eHarmony – claims to use a special type of machine learning to predict your taste and serve you a daily “Most Compatible” option. It supposedly uses the Gale-Shapley algorithm, which was created in 1962 by two economists who wanted to prove that any pool of people could be sifted into stable marriages. But Hinge mostly just looks for patterns in who its users have liked or rejected, then compares those patterns to the patterns of other users. Not so different from Tinder. Bumble, the swiping app that only lets women message first, is very close-lipped about its algorithm, possibly because it’s also very similar to Tinder.
Second, they found that dating apps in some way make it easier to communicate with those people
The League – an exclusive dating app that requires you to apply using your LinkedIn – shows profiles to more people depending on how well their profile fits the most popular preferences. The people who like you are arranged into a “heart queue,” in order of how likely the algorithm thinks it is that you will like them back. In that way, this algorithm is also similar to Tinder’s. To jump to the front of the line, League users can make a Power Move, which is comparable to a Super Like.
In a (pre-Tinder) 2012 study, a team of researchers led by Northwestern University’s Eli J
None of the swiping apps purport to be as scientific as the original online dating services, like Match, eHarmony, or OkCupid, which require in-depth profiles and ask users to answer questions about religion, sex, politics, lifestyle choices, and other highly personal topics. This can make Tinder and its ilk read as insufficient hot-or-not-style apps, but it’s useful to remember that there’s no proof that a more complicated matchmaking algorithm is a better one. In fact, there’s a lot of proof that it’s not.
Sociologist Kevin Lewis told JStor in 2016, “OkCupid prides itself on its algorithm, but the site basically has no clue whether a higher match percentage actually correlates with relationship success … none of these sites really has any idea what they’re doing – otherwise they’d have a monopoly on the market.”
Finkel examined whether dating apps were living up to their core promises. First, they found that dating apps do fulfill their promise to give you access to more people than you would meet in your everyday life. And third, they found that none of the dating apps could actually do a better job matching people than the randomness of the universe could. The paper is decidedly pro-dating app, and the authors write that online dating “has enormous potential to ameliorate what is for many people a time-consuming and often frustrating activity.” But algorithms? That’s not the useful part.