I always recommend looking at data in several different ways, to get a more complete picture of what's really going on - such is the case with the member 'ratings' on dating websites. Let's take a look at some data from a different angle...
In a recent blog post, I analyzed which age men & women the opposite sex rated most attractive. The graphs indicated that men rated 20-year-old women the most attractive, whereas women rated men closer to their own age most attractive. This sparked quite a bit of discussion (such as the comments in the cross-posting of the blog on allanalytics.com).
So I decided to look at the ratings data in a different way - this time ignoring age, and just looking at how men and women rate each other in general. I found some histograms on p. 16 of Christian Rudder's new book Dataclysm that showed almost what I was looking for, and I then used some graphs from his blog to estimate the data so I could create similar charts in SAS.
Whereas the men of all age groups consistently rated 20-year-old women the most attractive (which produced a very lopsided chart), their ratings of all women in general produced a very symmetrical chart. In Rudder's book he even describes it as "close to what's called a symmetric beta distribution - a curve often deployed to model basic unbiased decisions." Therefore it appears that men are very unbiased/honest in the way they rate women.
By comparison, women rated men very poorly. Rudder mentions that women only rate one guy in six as "above average."
What causes this huge difference in how men and women rate each other? Is one being more honest than the other? Are they rating based on different criteria (perhaps men are rating based on looks, and women are rating based on whether or not they think the men would make a good mate)? Perhaps women are hesitant to rate a man highly, because they know that will trigger okcupid to send that man a message letting them know which woman rated them highly? What other factors are perhaps influencing this data?
Feel free to leave your thoughts & theories on this topic in the comments section!