Ages ago (2013/2014?), when I was on tinder, I remember going through some generations of their algorithm. With their algorithm becoming increasingly hostile as the generations passed.

Gen N - whenever someone liked YOU, Tinder would immediately bring this person to the front of your like queue. This meant that if you hadn't used the app for say, in a day, then the first X persons presented would be people who liked you and you would get a bunch of matches.

Gen N+1 - Gen N was changed, such that maybe you'd get one match if you consistently liked the first 20 or so people in your queue. However, people who liked _you_ were not filtered out by the setting on your distance filter. So, you could set this filter to distance 1 KM, and basically get a list of matches to the forefront again.

Gen N+2 - the above hack was fixed, such that these likes would be filtered out as well (bastards). And then it felt like their algorithm became more and more hostile, post-poning presentation of people who liked you more and more. Basically, they really started to gamify the system, so that you would need to get these "power" boosts to get any matches at all apparently? I quit not long after this filter-hack was "fixed", so not sure what happened then.

The change you describe from N+1 to N+2 wasn’t made to defeat your hack. It was made because we got lots of complaints that people thought the filters were buggy/broken when they saw people who didn’t match their filters and because they were seeing irrelevant people, lowering the chance of a match. The set of people who already liked you were being served out of a different service than regular recommendations and it was, iirc, just a Redis list until fixed. (More generally, we never purposely made the recommendation algo worse to increase boosts or because people would only stay if they didn’t meet someone during my era, even if everyone thought that’s we did. I haven’t been involved in several years however.) In any case, sorry!

>More generally, we never purposely made the recommendation algo worse to increase boosts or because people would only stay if they didn’t meet someone during my era, even if everyone thought that’s we did.

Would anyone admit this publicly? That's a surefire way to destroy your career or getting sued.

Also begs the question for which performance indicators did you optimize if not engagement and retainment?

> From a cynical business POV it's in a dating app's best interest to not let you find a relationship and keep you spending money/watching ads.

https://teddit.net/r/LokiList/comments/s0a0w6/why_i_made_lok...

Why you should never pay for online dating

https://www.gwern.net/docs/psychology/okcupid/whyyoushouldne...

This reminded me that OKC used to blog about results and data a lot. Before they got bought by Match it really did seem like they had some interest in matching people. But it is also crazy now that of the 3 main apps (Tinder, Bumble, Hinge), Match owns 2 (Tinder and Hinge). The unfortunate part of all this is that network effects are essential to dating apps working, so it is hard to enter the space.