Hugh Pickens writes writes: "Remember when the Gay Girl in Damascus revealed himself as a middle-aged man from Georgia? On a platform like Twitter, which doesn't ask for much biographical information, it's easy (and fun!) to take on a fake persona but now linguistic researchers have developed an algorithm that can predict the gender of a tweeter based solely on the 140 characters they choose to tweet. The research is based on the idea that women use language differently than men. "The mere fact of a tweet containing an exclamation mark or a smiley face meant that odds were a woman was tweeting, for instance," reports David Zax. Other research corroborates these findings, finding that women tend to use emoticons, abbreviations, repeated letters and expressions of affection more than men and linguists have also developed a list of gender-skewed words used more often by women including love, ha-ha, cute, omg, yay, hahaha, happy, girl, hair, lol, hubby, and chocolate. Remarkably, even when only provided with one tweet, the the program could correctly identify gender 65.9% of the time. (PDF). Depending on how successful the program is proven to be, it could be used for ad-targeting, or for socio-linguistic research. "Marketing is one of the major motivators here," says linguist Delip Rao."
"Card readers? We don't need no stinking card readers."
-- Peter da Silva (at the National Academy of Sciencies, 1965, in a
particularly vivid fantasy)