dating

OKCupid, an online matchmaking site, offers data on gender and perceived attractiveness that I might use in my spring deviance course (via boing). The figures might help me make a Durkheimian society of (hot) saints point about the relative nature of beauty and a Goffman point on stigma affecting social interaction, while providing another illustration of the taken-for-grantedness of heteronormativity.

In any case, the first figure shows that male OKCupid ratings of female OKCupid users follows something like a normal distribution, with mean=2.5 on a 0-to-5 scale from “least attractive” to “most attractive.” Also, women rated as more attractive tend to get more messages. At first, I thought I saw evidence of positive deviance here, since women rated as most attractive get fewer messages than those rated somewhat below them — the 4.5s garner more attention than the 5.0s. But, as I’ll show below with the next chart, that would probably be an incorrect interpretation — confounding the “persons” in the dashed lines with the “messages” in the solid lines.

The next figure shows that female OKCupid users tend to rate most male OKCupid users as well below “medium” in attractiveness. According to OKCupid, “women rate an incredible 80% of guys as worse-looking than medium. Very harsh. On the other hand, when it comes to actual messaging, women shift their expectations only just slightly ahead of the curve, which is a healthier pattern than guys’ pursuing the all-but-unattainable.”

Hmm. The latter point isn’t wrong, I guess, but it shouldn’t obscure the bigger point that more attractive men still get more messages than less attractive men. Again, note that persons (OKCupid members) are the units of analysis for the dashed lines and messages (messages sent by OKCupid members) are the units for the solid lines. On first scan, I read the graph as suggesting that the top “attractiveness quintile” was getting fewer messages than the bottom attractiveness quintile — that uglier men were actually doing better than more attractive men — but that’s not the case at all. Instead, it just means that in the land of the hideous, the somewhat-less-than-loathsome man is king.

If almost everybody is rated as unattractive, most of the messages will go to those rated as unattractive. Nevertheless, the rate of messages-per-person still rises monotonically with attractiveness. As the “message multiplier” chart below shows, the most attractive men get about 11 times the messages of the least attractive men — and the most attractive women get about 25 times the messages of the least attractive women.

—————————

Chris Uggen is Distinguished McKnight Professor and Chair of Sociology at the University of Minnesota.  His writing appears in American Sociological Review, American Journal of SociologyCriminology, and Law & Society Review and in media such as the New York Times, The Economist, and NPR.  With Jeff Manza, he wrote Locked Out: Felon Disenfranchisement and American Democracy.

If you would like to write a post for Sociological Images, please see our Guidelines for Guest Bloggers.

I recently wrote a quite popular post, titled “What Do Women Want?”, based on data collected by the dating site OK Cupid (short story: women like it when men engage with their personality, not just their looks).  Mary S. sent in a link to some of their data on race and response rate, with some fascinating findings.

First, OK Cupid measured the compatibility of people of different races. They found that, by and large, race doesn’t impact compatibility scores:

Match-By-Race

Then they looked at response rates. When a man writes an inquiry email to a woman, what is the chance that that woman will write back?  Here is the data:

Reply-By-Race-Male

What this table shows is that race matters.  OK Cupid breaks it down:

Black women… are by far the most likely to reply to your first message. In many cases, their response rate is one and a half times the average, and overall black women reply about a quarter more often.

white males just get more replies from almost every group.

White women prefer white men to the exclusion of everyone else—and Asian and Hispanic women prefer them even more exclusively. These three types of women only respond well to white men. More significantly, these groups’ reply rates to non-whites is terrible. Asian women write back non-white males at 21.9%, Hispanic women at 22.9%, and white women at 23.0%. It’s here where things get interesting, for white women in particular. If you look at the match-by-race table before this one, the “should-look-like” one, you see that white women have an above-average compatibility with almost every group. Yet they only reply well to guys who look like them.

And how do men respond to women?

Reply-By-Race-Female

OK Cupid again:

Men don’t write black women back. Or rather, they write them back far less often than they should. Black women reply the most, yet get by far the fewest replies. Essentially every race—including other blacks—singles them out for the cold shoulder.

White guys are shitty, but fairly even-handed about it. The average reply rate of non-white males is 48.1%, while white guys’ is only 40.5%. Basically, they write back about 20% less often.

To sum, white men appear to have the most dating capital in the online dating world, while black women seem to have the least.  This means that white men can sit back and enjoy the adulation, while black women are required to do more outreach to men to get the same results.

This makes sense give the way in which race is gendered.

For more, read Restaurant Refugee’s experiment comparing  responses on OK Cupid to an identical profile with pictures of a white person and a person of color.

UPDATE: Duran2, Dave, and Assaf critiqued my comment about white men sitting back and enjoying the adulation as both inaccurate and unfair. Point taken. I apologize.

For more, see our posts on asymmetry in interracial marriage and how Asian women are marketed to white men.

—————————

Lisa Wade is a professor of sociology at Occidental College. You can follow her on Twitter and Facebook.