After about 60 manual swipes, the program has learned enough to start making choices for you -- at a speed you could not possibly replicate. If you have the time (and inclination), go ahead and build a Tinderbox for yourself.
You may never visit the Chainsaw Sisters Saloon again.
When Amazon recommends a camera for you, the camera has no say in the matter. Someone may be your perfect match, but there are any number of reasons the feeling might not be mutual.
That said, there is an axiom working in favor of all big dating algorithms: boys and girls are genetically predisposed to be attracted to one another and attempt to reproduce (otherwise none of us would be here).
This adds a bit of a twist to big data's role in big dating.
Sure, you can answer the 150 questions on and hope to be matched to your soul mate, or you can just play the numbers. It offers an exponential increase in opportunities over bar crawling.
“There is one fundamental problem with all of these algorithms,” said Eli Finkel, a psychologist at Northwestern University who studies relationships.
“They have set themselves up with an impossible task: They assume that they can take information from two people who are totally unaware of each other’s existence and determine whether they are compatible.
Even so, motivated programmers have created dozens of Tinderbots to increase their efficacy.
Some Tinderbots use game theory and others use brute force, but my favorite uses data science to achieve its goal.
A generation ago, most young men would have considered happy hour at the Chainsaw Sisters Saloon a target-rich environment. Most importantly, while the odds of "getting lucky" were low, they were nonzero.
So even if she said, "You're more likely to get struck by lightning than to go home with me," he could answer, "Awesome! " Millennials empirically know that bar crawling is for recreation -- not for archaic, time-wasting, low-percentage mating rituals.
No other app comes close to its market share, but there are plenty of other offerings.