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?
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
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.
>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-r... (2005+)
* https://www.microsoft.com/en-us/research/publication/trueski... (2018) (Citations: 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-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?
> 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.
If you sign up for Tinder as a guy, over 30, the premium and gold features are $29.99+, as someone under 27, it becomes 9.99-14.99, monthly before the discount of upfront charging.
Then they say they don't do Elo Score anymore, but I question that, if your profile is rated higher in a geographic location, and then you change location again, it will rank higher and be more apparent (to my own A/B testing.)
Then again the second part is totally my interpretation, it's a fun game, and the API is really annoying.
It's a fun time sink, I really wonder more of what other data collection they do. Imagine being able to export an entire list of users, by geographic location, who own cats (or have a cat present in photo, tensorflow) to CSV and then pivot table it.
Fantastic, scary fantastic.