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The less-messaged woman was usually considered consistently attractive, while the more-messaged woman often created variation in male opinion. We felt like were on to something, so, being math nerds, we put on sweatpants. Our first result was to compare the standard deviation of a woman's votes to the messages she gets.

We found that the more men disagree about a woman's looks, the more they like her. messages curve below, again including some examples.

The women along the graph are near the 80 Our next step was to analyze a woman's actual vote pattern of 1s, 2s, 3s, 4s, and 5s: This required a bit more math and is harder to explain with a simple line-chart.

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(This happens all the time in China.) men think you're ugly, other men are more likely to message you. To the typical man considering her, she's obviously attractive enough to create the impression that guys are into her, too.And when some men think you're cute, other men become less interested. Perhaps a little game theory can explain: Suppose you're a man who's really into someone. maybe she's just waiting to find a guy who appreciates her. But maybe she's hot enough for him to throw caution (and grammar) to the wind and send her a message. The overall picture looks something like this: do, what does all the above analysis mean in practical terms?Ok Cupid uses a 1 to 5 star system for rating people, so the rest of our discussion will be in those terms.All the users pictured were generous and confident enough to allow us to dissect their experience on our site, and we appreciate it. As you can see, though the average attractiveness for the two women above is very close, their vote patterns differ.With this we can translate into how much attention she actually gets.

The equation we arrived at might look opaque, but when we get into it, we'll see it says some funny things about guys and how they decide which women to hit on.

These graphs are adjusted for race, location, age, profile completeness, login activity, and so on—the only meaningful difference between the people plotted is their looks.

After running a bunch of these, we began to ask ourselves: what else accounts for the wide spread of the x's, particularly on the "above-average" half of the graph? If all we know is that she is a 7, there's no way to tell.

This is a pretty crazy result, but every time we ran the numbers—changing the constraints, trying different data samples, and so on—it came back to stare us in the face. You send her the perfectly crafted opening message.

In plain scientific terms, it was like a baby we were trying to drown had somehow grown gills. On the other hand, a woman with a preponderance of '4' votes, someone conventionally cute, but not totally hot, might appear to be more in-demand than she actually is.

On the left you have consensus, and on the right you have split opinion.