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Opposites attract. The data reveals a clear pattern: People are interested in people like themselves. Women on eHarmony favor men who are similar not just in obvious ways — age, attractiveness, education, income — but also in less apparent ones, such as creativity. In fact, of the traits in the data set, there was not one for which women were more likely to contact men with opposite traits.
Men were a little more open-minded. For 80 percent of traits, they were more willing to message those different from them. Men showed no such preference. There are some nuances here. Since eHarmony publicizes this fact, the site may well attract online daters who are sympathetic to its philosophy. The eHarmony data I used is incomplete: It includes no gay couples, because eHarmony does not make same-sex matches on its main site.
He also noted that there were differences in what traits matter to gay people, something the online dating site OkCupid has also found: Gay men and women differ from straight people in their racial preferencesfor example. Before feeding their choices into its algorithm, eHarmony asks users to rate how strongly they feel about nine traits — among them age, ethnicity and religion — and women express stronger preferences for every one.
This got me wondering, how self-aware are people in general?
Does what they claim they care about align with their messaging behavior? It often does. People with high incomes and high degrees of education claim that income and education matter to them more, and they display an especially large messaging preference for potential mates with high incomes and educations. But for other traits people appear to be confused, or lying. People of every age claim that age matters to them about the same amount — they rate it about 4. Everyone claims that ethnicity matters to them about the same amount 4. This remained true even when I controlled for attractiveness, age and whether the woman messaged the man, and even when I looked only at men who rated their drinking preference as important.
Height illustrates both these patterns. Men follow the first: Short men prefer short women, and tall men prefer tall women.I asked her the question...
Women follow the second: All women prefer taller men, but tall women display a stronger preference for tall men. Men follow the second pattern: All men prefer women who describe themselves as intelligent, but men who describe themselves as intelligent display a stronger preference.
In general, widely considered positive traits, 5 like attractiveness or physical fitness, tend to follow the second pattern: Everyone prefers hotter, fitter people, but hot, fit people show a stronger preference for people like them. On the other hand, traits whose optimal value is more arguable — like whether you have children or what religion you follow — tend to follow the first pattern. Those with children preferred those with children; those without preferred those without.
And people generally prefer those of their own religion. But even here, the data failed me. The sugar daddy stereotype fails in other ways as well. Women who message ificantly older men were calculated to be less attractive than those men, and I could find no evidence that they cared more about income, or less about attractiveness, than women paired with men their own age. I also looked for opposites attracting in other online dating data. I spoke to Christian Rudder, founder of OkCupid, which has a rich and idiosyncratic data set.
Perhaps the most striking confirmation of the idea that birds of a feather flock together comes from the data of 23andMethe genetics company where I work. Here, too, my 23andMe colleague Aaron Kleinman and I found that birds of a feather flock together: For 97 percent of the traits we examined, couples were positively correlated.
Former smokers tended to pair with former smokers, the apologetic with the apologetic, the punctual with the punctual. We also found some examples where opposites attracted: Morning people tended to pair with night owls, and people with a good sense of direction with those who lacked one. There are at least three reasons we so often message and eventually mate with the similar. When we are exposed to matches, we tend to pursue people who are similar.
And after we start dating, we may grow to be even more alike. But even believers in algorithmic approaches to love acknowledge these shadows exist. The scientists I spoke to at eHarmony and OkCupid agreed. As rich as their data sets are, the uncertainty of that first meeting remains. Correction April 10 p.
I looked at the s of all the product terms, as well as how statistically ificant they were, and could not find any interesting cases where opposites attracted after using the Bonferroni correction for the of traits examined.
I experimented with a few different models to ensure my basic conclusions stayed the same. I tried looking at each trait individually but controlling for obvious factors by which people choose to message mates — attractiveness, age and whether the person messaged them. I tried making the continuous variables binary by whether they were above average. Finally, because many of these variables are correlated, I ran a giant regression including the value of every trait along with interactions simultaneously.
None of these mathematical modifications persuaded opposites to get together, and the last one containing variables and 1 million couples crashed my computer. I reran that regression usingcouples. The rest of the traits are self-reported by users. This is not because men are just more willing to message everyone — I controlled for that by looking at the difference in rates at which men messaged women who were similar and women who were different.
For his complex but lovely discussion of the subject, see here. Emma Pierson writes about statistics at her blog, Obsession with Regression. Sorry, your blog cannot share posts by .Sex dating in Pierson
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