Using your browser URL history to estimate gender

Mike On Ads developed this interesting algorithm that tries to determine your gender by analyzing your web browsing history. Very cool and eerily accurate in my case.

Likelihood of you being FEMALE is 0%
Likelihood of you being MALE is 100%

Site	Male-Female Ratio
google.com	0.98
amazon.com	0.9
paypal.com	1.04
apple.com	0.89
dell.com	1.04
digg.com	1.56
shopping.com	0.96
cnet.com	1.56
com.com	1.41
gizmodo.com	2.08
lifehacker.com	1.63
newegg.com	2.23
slickdeals.net	1.27
kotaku.com	1.94
frys.com	1.6
engadget.com	1.7
joystiq.com	1.44
lenovo.com	1.67
valleywag.com	1.7
destructoid.com	2.17
ecogeek.org	2.45

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One Response to “Using your browser URL history to estimate gender”

1. Anatoli says:

   August 18, 2008 at 1:27 pm

   HAHA… check this out, a pretty good guess:

   Likelihood of you being FEMALE is 14%
   Likelihood of you being MALE is 86%

   Site Male-Female Ratio
   google.com 0.98
   verizonwireless.com 0.77
   digg.com 1.56
   gamespot.com 1.15
   lifehacker.com 1.63
   newgrounds.com 0.85
   gametrailers.com 1.53
   pandora.com 0.9
   fark.com 1.82
   gmail.com 0.9
   kongregate.com 1.41