January 26, 2014
Posted by Jay Livingston
The useful thing about cultural stereotypes is that to some degree, they’re often accurate – a convenient shorthand.
(Sorry about the lousy sound, but this was the best clip I could find, and it does have subtitles.)
The Woody Allen character learns her name, her thesis topic . . . and all the rest follows. Note also that Allison (my neighbor Carol Kane) doesn’t say that Woody is incorrect.
What reminded me of “Annie Hall” (the Annie character too is a cultural stereotype) was this:
(Click on an image for a larger view.)
The three axes are percentages:
- Width - seeking a one-night stand
- Depth - had same-gender sex
- Height - say God is important to them)
The graph is a typology of women – women on OK Cupid, the dating site founded by four Harvard math majors.* The graph appears in
this Wired article about Chris McKinlay, a 35-year old guy who took nerditude to the n+1
th degree, creating bots to Hoover up data on responses to the hundreds of questions OK Cupidians can answer.** Eventually, he had six million answers from 20,000 women. But how to analyze the big data?
A modified Bell Labs algorithm called K-Modes. First used in 1998 to analyze diseased soybean crops, it takes categorical data and clumps it like the colored wax swimming in a Lava Lamp. With some fine-tuning he could adjust the viscosity of the results, thinning it into a slick or coagulating it into a single, solid glob.
He played with the dial and found a natural resting point where the 20,000 women clumped into seven statistically distinct clusters based on their questions and answers.
The names of the clusters –Tattoo, Dog, etc. – are basically cultural stereotypes.
In the younger cluster, the women invariably had two or more tattoos and lived on the east side of Los Angeles. In the other, a disproportionate number owned midsize dogs that they adored.
The article also has graphics on how the seven stereotypes differed from one another in four areas. (The “Green” tag is not political; Greens are merely recent arrivals at OK Cupid. They are also the most sexually adventurous. As the placement of the green ball on the graph shows, 50-60% would be comfortable with a one-night hook-up, and 40-50% have had same gender sex. Not surprisingly, they do not find God to be an important part of their lives.)
The stereotypes, based on clusters, were very useful for finding, well, clusters. McKinlay tailored his two OK Cupid profiles to maximize his chances of getting a response so he would do better than the six OK Cupid dates he’d managed to get in the previous nine months. He did. His scientifically customized profile was getting 400 hits a day.
Cultural stereotypes may get you into the right room (and save you a lot of time wandering into wrong rooms), but they’re no guarantee of compatibility with an actual person. McKinlay went on more than 50 first dates – a big improvement over six in nine months – but only a handful of these led to a second date, and none went further.
Given this data, most of us would figure that it was time to start thinking about our interpersonal skills or perhaps our grooming and hygeine. Wired says merely that McKinlay “had to question his calculations.”
But finally, something clicked, and the story seems to be heading towards a happy ending – a year-long relationship, some of it long-distance since the woman is on a one-year fellowship in Qatar.
on one of their daily Skype calls . . . McKinlay pulls out a diamond ring and holds it up to the webcam. She says yes.
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* Previous posts on OK Cupid are
here and
here.
** The technical details:
he set up 12 fake OkCupid accounts and wrote a Python script to manage them. The script would search his target demographic (heterosexual and bisexual women between the ages of 25 and 45), visit their pages, and scrape their profiles for every scrap of available information: ethnicity, height, smoker or nonsmoker, astrological sign—“all that crap,” he says.
The phrase “Python script” of course poses a tremendous challenge for me to avoid the obvious joke – surely one made so often that it has long been an ex-joke.