"The fox knows many things, but the hedgehog knows one big thing."

                --Archilochus

Glenn Reynolds:
"Heh."

Barack Obama:
"Impossible to transcend."

Albert A. Gore, Jr.:
"An incontinent brute."

Rev. Jeremiah Wright:
"God damn the Gentleman Farmer."

Friends of GF's Sons:
"Is that really your dad?"

Kickball Girl:
"Keeping 'em alive until 7:45."

Hired Hand:
"I think . . . we forgot the pheasant."




I'm an
Alcoholic Yeti
in the
TTLB Ecosystem



Monday, February 07, 2011

TMI

Researchers at Carnegie Mellon University's School of Computer Science turned their trusty computers loose to crash through the underbrush of the Twitter Universe, and have found something a bit strange.  While one would think that the Internet creates a community unconnected to the actual non-virtual geographic location of the speaker, that turns out to be false;  Tweeters have regional dialects:
Postings on Twitter reflect some well-known regionalisms, such as Southerners' "y'all," and Pittsburghers' "yinz," and the usual regional divides in references to soda, pop and Coke. But Jacob Eisenstein, a post-doctoral fellow in CMU's Machine Learning Department, said the automated method he and his colleagues have developed for analyzing Twitter word use shows that regional dialects appear to be evolving within social media.

In northern California, something that's cool is "koo" in tweets, while in southern California, it's "coo." In many cities, something is "sumthin," but tweets in New York City favor "suttin." While many of us might complain in tweets of being "very" tired, people in northern California tend to be "hella" tired, New Yorkers "deadass" tired and Angelenos are simply tired "af."

The "af" is an acronym that, like many others on Twitter, stands for a vulgarity. LOL is a commonly used acronym for "laughing out loud," but Twitterers in Washington, D.C., seem to have an affinity for the cruder LLS.

Eisenstein said some of this usage clearly is shaped by the 140-character limit of Twitter messages, but geography's influence also is apparent. The statistical model the CMU team used to recognize regional variation in word use and topics could predict the location of a microblogger in the continental United States with a median error of about 300 miles.
Story HERE, full paper HERE.

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