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ing work?" seems to be: "Not the way it pre-
tends to work."
SensitiveDude had not expressed any
preferences when it came to the height, eth-
nicity, salary, or body type of his potential
dates. "Surprise me!" I thought.
But in the first batch of suggested dates,
the matches seemed to have less in com-
mon with the Dude than with each other.
That set included a short 23-year-old Jew-
ish woman with a cute photo of herself at a
fancy restaurant and two others of herself
on the arms of guys. She liked the Econo-
mist but also Us Weekly. Her favorite things
included "brunch." The site said we had been
matched because we were both dog lovers,
eldest children, and athletic and toned.
The second match, too, the site said, was
deemed compatible on the basis of birth
order and pet preferences. But I noted that
she was also Jewish, also young (24), and
also short, at five foot two. "Seats at a Yank's
[sic] game are always a winner with me," her
"About Me" section declared. This assertion
was reinforced by a photo of her in a jersey
at a baseball game. Another photo showed
her posing in panties and a tank top.
I clicked "maybe" when the site asked
me to say whether I was interested in her,
and then I clicked "maybe" on a couple of
the other short young Jews---not wanting to
click "yes," which would have automatically
informed the women of my interest. But one
woman who'd been shown my profile in her
top 5 did click "yes," so I checked her out.
She was a 24-year-old lab tech at a fertil-
ity clinic, with an incoherent, heavily mis-
spelled profile. She loved malls and hated
country music, and her profile photograph
was an odd shot of her sucking on a straw.
The site, seeming desperate to find some-
thing we had in common, pointed out, "Like
you, she's never been married!" I looked at
my own profile to remind myself that I was
no prize, but then I shut my laptop. I was
beginning to understand the basis of the
distrust I'd felt when Ruby joined Match. It
was gross to know that actual men sat there
as I'd just done, flipping through photos of
women so desperate for their attention that
they posted photos of themselves in bathing
suits, twisting around to accentuate their
butts while delivering soft-porn smiles.
All this is big business. Online dating,
according to Forrester Research, produced
$957 million in revenue in 2008---making it
the third-largest generator of online paid-
content revenue, after music download-
ing and gaming---and is expected to grow
another 10 percent annually through 2013.
Even (or especially) in the face of economic
contraction, Match.com is thriving.
As a man on Match, I had the sense that
what I was doing was a kind of online shop-
ping, which makes sense. The site uses the
same type of data-mining technique, called
latent semantic indexing (LSI), that search
engines like Google use to rank the rele-
vance of Web pages.
The trick behind successfully matching
people and products---or people and other
people, or people and other people who've
packaged themselves into something like
products by means of "profiles"---is math.
"You and I don't imagine four-dimensional
spaces, but mathematics and computers
can," says David Jacobs, a vice president at
the blogging-platform company SixApart,
who's worked with similar technology in
designing social-media sites. "Each addi-
tional attribute considered creates an extra
dimension in the 'space' with which Match
.com is looking for matches. The algorithm
creates a virtual graph which approximates
hundreds or thousands of axes."
That's straightforward. But the other half
of the trick is not: it has to do with analyzing
the way customers browse rather than the
rankings and feedback they deliver. It's the
di erence between recommending a match
for SensitiveDude450 because we're "both
eldest children" and recommending a match
because the site knows that users like Sen-
sitiveDude click on the profiles of women
who make a bit less money, are shorter, and
share the same religion.
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