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> That's why you should delete and recreate your profile several times to skew up the analytics Don't do this. A friend got banned for deleting account a lot o

> That's why you should delete and recreate your profile several times to skew up the analytics Don't do this. A friend got banned for deleting account a lot of times. Also, I don't see any problem in using ELO. Because of skewed gender ratio on dating apps problems exist; but it makes sense to show most profiles in similar normalized ELO ranges. Isn't that how most humans pick their date in online world anyway?

Nextgrid 6y ago
What's the downside of a ban on Tinder though? Can't you just recreate an account again and again anyway? The worst you have to lose is a burner phone number.
- durnygbur 6y ago
  You have no idea. The Tinder ban applies to the entire fingerprint consisting of at least: phone number, Google/iCloud account (used with the app store), physical device. Then it creeps over, e.g. using another device and phone number but the same Google/iCloud account incorporates the first two into the banned fingerprint, using another phone number from the same physical device incorporates the phone number into the banned fingerprint. Discussions on Reddit claim that they use the WiFi SSID for fingerprinting as well. It's really creepy.
  - joshspankit 6y ago
    Graphs and nodes: Very few people understand the possibilities when software can take a single record of two things being connected, and connect the dots with everything else they already know about you.
polote 6y ago
Yeah that doesnt work anymore, if you recreate your profile several time, you wont get banned, but you will be granted a low ELO score for life. And don't try to create a new account with a new phone number of new facebook account, they also match old accounts with the phone itself. Bumble is doing the same. If you want to recreate your account, you need, a new facebook account, but with friends on it, otherwise they know it is a fake one, a new number, a new phones and new pictures. So easy to say that this is impossible
- lozaning 6y ago
  We've got vastly different understandings of what is impossible.
- rootsudo 6y ago
  I've noticed this. It's really hard for social reputation and dependence for Google/Apple ID/Facebook for that web SSO feature. e-sim works, but you can't fall on a cheap sim. But it makes sense, age of facebook account, number of friends, pictures.. I wonder if they checksum/hash pictures.
no_identd 6y ago
>I don't see any problem in using ELO. >it makes sense to show most profiles in similar normalized ELO ranges Let me highlight (but not explicitly point out, so you may mentally connect the dots yourself) the exact problem with both of these statements: Suppose the 'logic' of whatever meta-algorithm one implicitly presupposes as behind picking the desiderata for picking the appropriate algorithm to use for the problem as principally sound. Then, by extension WOLG, it NOWADAYS actually makes no sense at all to continue using ELO, because significantly better algorithms have long since come along. Two by now both ancient examples, check the first one for why & how ELO sucks even for its original intended usage, and check the second one for a tremendously improved version: * https://www.microsoft.com/en-us/research/project/trueskill-ranking-system/ https://www.microsoft.com/en-us/research/project/trueskill-r... (2005+) * https://www.microsoft.com/en-us/research/publication/trueskill-2-improved-bayesian-skill-rating-system/ https://www.microsoft.com/en-us/research/publication/trueski... (2018) (Citations: https://scholar.google.com/scholar?cites=10179469592728174863 https://scholar.google.com/scholar?cites=1017946959272817486...) Oh and, as one may guess, neither of these examples represents the State of the Art in this sector (Check the citations above for that.). Also, for more papers by the Microsoft Research group working on that project, check here: https://www.microsoft.com/en-us/research/project/trueskill-ranking-system/#!publications https://www.microsoft.com/en-us/research/project/trueskill-r... Now that we've clarified that, I'd like to ask: Do you still feel sure whether this seems like an appropriate class of algorithms to leverage for dating? Assuming of course that users want to find partners, as opposed to good opponents. Albeit: One might speculate algorithmically supplying well-matching opponents instead of potential partners, while (mis)labeling them as more potentially likely compatible than by chance partners would make for a tremendously better—albeit highly amoral—repeat business model on part of the platforms, at least in the relative short-term, wouldn't you say?
- actuator 6y ago
  If your argument is that there are better 'rating' algorithms than ELO which can be used. Sure, go ahead and use them. I wasn't championing ELO specifically. I meant any rating algorithm which can theoretically rank individuals. Obviously, no solution of ranking individuals on the concept of wins/losses is going to be perfect. Btw, I had the luck of implementing the bayesian Trueskill system you mentioned in some product I worked on. > Do you still feel sure whether this seems like an appropriate class of algorithms to leverage for dating? Assuming of course that users want to find partners, as opposed to good opponents. Imagine there being `n` heterosexual males and `n` heterosexual females on a dating platform. If all have to be paired as couples and if we can rank them by their 'popularity'. Don't you think most at the first glance would be more comfortable picking someone about their rating or higher? Just look at the skew of likes people get depending on their attractiveness from old OkCupid blogs. In dating apps, the rating most likely comes from the person's looks. Does that mean they are good matches? No way of knowing this. But does that mean they are more likely to swipe on each other? Probably yes. We can show them people at random but that doesn't mean that they will swipe on someone whom they don't consider to be at least in the same ballpark as them on attractiveness. The only way we can get better potential partners is if we have a lot of potential data about every user not limited to just looks. Also, even in that case if the other person is not on the same scale on attractiveness, the other person will have to take a leap of faith on whatever matching system they have.(which if you go by social experiments, people don't do) Considering how much data FB has about users through their platforms, they are the ones who truly can come close to matching people on common interests but I am not sure how successful even their dating venture has been.

Nextgrid 6y ago

What's the downside of a ban on Tinder though? Can't you just recreate an account again and again anyway? The worst you have to lose is a burner phone number.

durnygbur 6y ago
You have no idea. The Tinder ban applies to the entire fingerprint consisting of at least: phone number, Google/iCloud account (used with the app store), physical device. Then it creeps over, e.g. using another device and phone number but the same Google/iCloud account incorporates the first two into the banned fingerprint, using another phone number from the same physical device incorporates the phone number into the banned fingerprint. Discussions on Reddit claim that they use the WiFi SSID for fingerprinting as well. It's really creepy.
- joshspankit 6y ago
  Graphs and nodes: Very few people understand the possibilities when software can take a single record of two things being connected, and connect the dots with everything else they already know about you.

polote 6y ago

Yeah that doesnt work anymore, if you recreate your profile several time, you wont get banned, but you will be granted a low ELO score for life. And don't try to create a new account with a new phone number of new facebook account, they also match old accounts with the phone itself. Bumble is doing the same. If you want to recreate your account, you need, a new facebook account, but with friends on it, otherwise they know it is a fake one, a new number, a new phones and new pictures. So easy to say that this is impossible

lozaning 6y ago
We've got vastly different understandings of what is impossible.
rootsudo 6y ago
I've noticed this. It's really hard for social reputation and dependence for Google/Apple ID/Facebook for that web SSO feature. e-sim works, but you can't fall on a cheap sim. But it makes sense, age of facebook account, number of friends, pictures.. I wonder if they checksum/hash pictures.

no_identd 6y ago

>I don't see any problem in using ELO. >it makes sense to show most profiles in similar normalized ELO ranges Let me highlight (but not explicitly point out, so you may mentally connect the dots yourself) the exact problem with both of these statements: Suppose the 'logic' of whatever meta-algorithm one implicitly presupposes as behind picking the desiderata for picking the appropriate algorithm to use for the problem as principally sound. Then, by extension WOLG, it NOWADAYS actually makes no sense at all to continue using ELO, because significantly better algorithms have long since come along. Two by now both ancient examples, check the first one for why & how ELO sucks even for its original intended usage, and check the second one for a tremendously improved version: * https://www.microsoft.com/en-us/research/project/trueskill-ranking-system/ https://www.microsoft.com/en-us/research/project/trueskill-r... (2005+) * https://www.microsoft.com/en-us/research/publication/trueskill-2-improved-bayesian-skill-rating-system/ https://www.microsoft.com/en-us/research/publication/trueski... (2018) (Citations: https://scholar.google.com/scholar?cites=10179469592728174863 https://scholar.google.com/scholar?cites=1017946959272817486...) Oh and, as one may guess, neither of these examples represents the State of the Art in this sector (Check the citations above for that.). Also, for more papers by the Microsoft Research group working on that project, check here: https://www.microsoft.com/en-us/research/project/trueskill-ranking-system/#!publications https://www.microsoft.com/en-us/research/project/trueskill-r... Now that we've clarified that, I'd like to ask: Do you still feel sure whether this seems like an appropriate class of algorithms to leverage for dating? Assuming of course that users want to find partners, as opposed to good opponents. Albeit: One might speculate algorithmically supplying well-matching opponents instead of potential partners, while (mis)labeling them as more potentially likely compatible than by chance partners would make for a tremendously better—albeit highly amoral—repeat business model on part of the platforms, at least in the relative short-term, wouldn't you say?

actuator 6y ago
If your argument is that there are better 'rating' algorithms than ELO which can be used. Sure, go ahead and use them. I wasn't championing ELO specifically. I meant any rating algorithm which can theoretically rank individuals. Obviously, no solution of ranking individuals on the concept of wins/losses is going to be perfect. Btw, I had the luck of implementing the bayesian Trueskill system you mentioned in some product I worked on. > Do you still feel sure whether this seems like an appropriate class of algorithms to leverage for dating? Assuming of course that users want to find partners, as opposed to good opponents. Imagine there being `n` heterosexual males and `n` heterosexual females on a dating platform. If all have to be paired as couples and if we can rank them by their 'popularity'. Don't you think most at the first glance would be more comfortable picking someone about their rating or higher? Just look at the skew of likes people get depending on their attractiveness from old OkCupid blogs. In dating apps, the rating most likely comes from the person's looks. Does that mean they are good matches? No way of knowing this. But does that mean they are more likely to swipe on each other? Probably yes. We can show them people at random but that doesn't mean that they will swipe on someone whom they don't consider to be at least in the same ballpark as them on attractiveness. The only way we can get better potential partners is if we have a lot of potential data about every user not limited to just looks. Also, even in that case if the other person is not on the same scale on attractiveness, the other person will have to take a leap of faith on whatever matching system they have.(which if you go by social experiments, people don't do) Considering how much data FB has about users through their platforms, they are the ones who truly can come close to matching people on common interests but I am not sure how successful even their dating venture has been.