Rather than making up numbers, check out their linear regression model:
msgs = .4m1-.5m2-.1m4+.9m5+k
4s (“eh, cute”) get asked out less. 5s (“hot”) get asked out more. 1s (“weird”) get asked out more, because somebody thought that was a five, and rather than a supermodel who must be inundated with messages, it’s someone quirky whose average rating is only a 3 (and thus approachable).
and rather than a supermodel who must be inundated with messages, it’s someone quirky whose average rating is only a 3 (and thus approachable)
That’s the hypothesis that OkCupid advanced: game-theoretically, it makes sense to go for people you are strongly into who other people aren’t into. But there’s a problem with this hypothesis: it could turn out to be true, but right now, it’s sort of silly.
It’s unnecessary. Look at some normal distributions, and it’s easy to see that having a high variance of attractiveness is sufficient to explain high positive responses (that motivate 5-ratings and messaging) and highly negative responses (that motivate 1-ratings). Let’s say you message a woman with high variance (lots of 5s, lots of 1s) who you consider a five. Maybe that’s because for you, she isn’t actually a 5, she’s a 6! But the scale only goes to 5 inducing a ceiling effect. You are going for her because you are really, really into her (for the same reasons that other guys are really, really not into her), not because you anticipate less competition.
There is no evidence that people are thinking of that sort of game theory. It’s possible, but if men really cared so much about minimizing competition, you’d think they would message women they found 3s and 4s more often.
If you think someone is a 5, even due to high variance traits that other guys hate, you don’t necessarily realize that other guys hate those traits (typical mind fallacy). Instead, you may assume that other guys would be into her just as much as you, which undermines the notion that you are trying to get the women that other guys won’t pursue. This hypothesis gives men too much credit predicting the psychology of other men, and calculating the average appeal of a woman across the whole male population. For instance, I can’t figure out what the guys who give flower-hair-girl a 1-rating are smoking.
Assortive mating. If you message a woman with tattoos and piercings (to use the example in the article), is that because you are thinking “aha! tats and piercings will turn off other guys, so I’ll have her all to myself,” or “wow, I really like that she has tattoos and piercings, and she is probably going to like my tattoos and piercings, too!” This hypothesis isn’t really supported or necessary either, but it helps why men don’t treat all 5s (from their perspective) equally. If someone has tribal markers, it explains why you might both find them a 5 a message them, while you are less likely to message another woman you rate a 5 without tribal markers, and why other guys from other tribes can’t stand women with the affiliations you like.
It’s unnecessary. Look at some normal distributions, and it’s easy to see that having a high variance of attractiveness is sufficient to explain high positive responses (that motivate 5-ratings and messaging) and highly negative responses (that motivate 1-ratings).
Emphasis mine. Is there a difference between this and “quirky”?
I think you were on the right track with the word “quirky.” It was the OkCupid article’s game theoretic hypothesis that I was objected (referenced by avoiding people “inundated with messages” in your comment).
Numbers were made up because people rating someone a 4 don’t give them negative attention (as in intercepting messages), so much as something more like give them less attention than average given their attractiveness level.
It may actually give them negative attention; suppose I don’t message anyone I rate a 4 (I don’t) and by raising their rating I make others less likely to message them (because their average rating is higher). (I thought there was a way to determine another user’s average rating, but I’m not seeing it from a quick check of the site, so this may not be the case.)
To the best of my knowledge, though, the coefficient for m4 and m2 aren’t “relative to m3” but absolute; if someone gets 10 5s, they’re expected to get 9 messages. If they got 9 4s and a 5, they’re expected to get no messages. (Of course, what would be interesting is looking at clusters rather than just linearly regressing the data.)
Rather than making up numbers, check out their linear regression model:
msgs = .4m1-.5m2-.1m4+.9m5+k
4s (“eh, cute”) get asked out less. 5s (“hot”) get asked out more. 1s (“weird”) get asked out more, because somebody thought that was a five, and rather than a supermodel who must be inundated with messages, it’s someone quirky whose average rating is only a 3 (and thus approachable).
That’s the hypothesis that OkCupid advanced: game-theoretically, it makes sense to go for people you are strongly into who other people aren’t into. But there’s a problem with this hypothesis: it could turn out to be true, but right now, it’s sort of silly.
It’s unnecessary. Look at some normal distributions, and it’s easy to see that having a high variance of attractiveness is sufficient to explain high positive responses (that motivate 5-ratings and messaging) and highly negative responses (that motivate 1-ratings). Let’s say you message a woman with high variance (lots of 5s, lots of 1s) who you consider a five. Maybe that’s because for you, she isn’t actually a 5, she’s a 6! But the scale only goes to 5 inducing a ceiling effect. You are going for her because you are really, really into her (for the same reasons that other guys are really, really not into her), not because you anticipate less competition.
There is no evidence that people are thinking of that sort of game theory. It’s possible, but if men really cared so much about minimizing competition, you’d think they would message women they found 3s and 4s more often.
If you think someone is a 5, even due to high variance traits that other guys hate, you don’t necessarily realize that other guys hate those traits (typical mind fallacy). Instead, you may assume that other guys would be into her just as much as you, which undermines the notion that you are trying to get the women that other guys won’t pursue. This hypothesis gives men too much credit predicting the psychology of other men, and calculating the average appeal of a woman across the whole male population. For instance, I can’t figure out what the guys who give flower-hair-girl a 1-rating are smoking.
Assortive mating. If you message a woman with tattoos and piercings (to use the example in the article), is that because you are thinking “aha! tats and piercings will turn off other guys, so I’ll have her all to myself,” or “wow, I really like that she has tattoos and piercings, and she is probably going to like my tattoos and piercings, too!” This hypothesis isn’t really supported or necessary either, but it helps why men don’t treat all 5s (from their perspective) equally. If someone has tribal markers, it explains why you might both find them a 5 a message them, while you are less likely to message another woman you rate a 5 without tribal markers, and why other guys from other tribes can’t stand women with the affiliations you like.
Emphasis mine. Is there a difference between this and “quirky”?
I think you were on the right track with the word “quirky.” It was the OkCupid article’s game theoretic hypothesis that I was objected (referenced by avoiding people “inundated with messages” in your comment).
Gotcha. I saw their game theory as justifying why people think quirkiness is (sometimes) attractive, not something people are consciously doing.
Numbers were made up because people rating someone a 4 don’t give them negative attention (as in intercepting messages), so much as something more like give them less attention than average given their attractiveness level.
It may actually give them negative attention; suppose I don’t message anyone I rate a 4 (I don’t) and by raising their rating I make others less likely to message them (because their average rating is higher). (I thought there was a way to determine another user’s average rating, but I’m not seeing it from a quick check of the site, so this may not be the case.)
To the best of my knowledge, though, the coefficient for m4 and m2 aren’t “relative to m3” but absolute; if someone gets 10 5s, they’re expected to get 9 messages. If they got 9 4s and a 5, they’re expected to get no messages. (Of course, what would be interesting is looking at clusters rather than just linearly regressing the data.)
Fair point, that works too.