http://www.mikeonads.com/2008/07/13/using-your-browser-url-history-estimate-gender/:

Using your browser URL history to estimate gender
July 13th, 2008

Thanks to Paul Cook for the initial link to this fascinating little javascript script Social History. Thes cript analyzes the css color of various links to determine whether or not the user has been to that site. If the link has the “visited” style, then he marks the user as having been to that site. Now the Social History implementation of this is rather innocuous — it’s a clever way of only displaying only the sharing buttons of sites that the user is an active participant of. Of course there are far more interesting applications for advertising.

One of the things that I always wanted to do but never got around to was to analyze a user’s browsing history to estimate age and gender. Of course the idea is definitely not new, in fact Xerox (of all companies??) has a patent on the whole process and I’m certain plenty of networks already do something of the sort… but what the heck, let’s have some fun!

So what I did is I modified the SocialHistory JS so that it polled the browser to find out which of the Quantcast top 10k sites were visited. I then apply the ratio of male to female users for each site and with some basic math determine a guestimate of your gender. The math is really quite simple, I just take:
1 / (1 + r_1 * r_2 * … * r_n)

where p_i is the ratio of men-to-women for the specific site. For example, if you had been to two sites that had a 2-1 ratio of men to women, the probability of you being female would be:
1 / (1 + 2 * 2) = 1/5 = 20%
Ok, so Click the button to give it a shot (those of you using RSS readers probably need to click this link to open this post in a browser):

UPDATE: This takes a while on Internet Explorer — please be patient (or try FireFox)

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

stimmt, LOL;-)

Na, ich will nicht wissen welche Schlagworte zu dieser Auswertung geführt haben.

Ich bin also eine Frau, und zwar, weil ich youtube.com, amazon.com, apple.com, mac.com und gmail.com besucht habe. Aha??

Mit einer größeren Datenbanl wäre das sicher lustiger …

Likelihood of you being FEMALE is 39%
Likelihood of you being MALE is 61%

ups... ich tendiere wohl auch schon Richtung Frau....

Likelihood of you being FEMALE is 23%
Likelihood of you being MALE is 77%

Likelihood of you being FEMALE is 32%
Likelihood of you being MALE is 68%

passt

Likelihood of you being FEMALE is 46%
Likelihood of you being MALE is 54%

Äh..interessant. Mal schaun, wie bewertet wird:

Site Male-Female Ratio
usps.com 0.9
archive.org 1.11
neimanmarcus.com 0.54
mozilla.org 1.33
ebay.de 1.63

Haha, das sind ja gerade mal 5 Domains und wenn bei einer war ich nicht besonders häufig, sondern wollte nur mal gucken, was es da so gibt.

Jedenfalls ist so ein Test ohne Gewichtung über Besuchszahlen wenig aussagekräftig. Auch kann man z.B. auf mozilla.org auch kaum das voreingestellte Stylesheet wechseln. Will man da hin benutzt man zwangsläufig deren CSS. Ähnliches gilt bei eb*y, oder haben die keine weibliche Kundschaft?