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Why is this linguist #talmbout Twitter?

A case study on Twitter dialect. Plus, a video profile of the UMass linguist.

Lisa Green
John Solem

The lickety-split spread of the phrase stay woke is just one linguistic development you can clearly track via Twitter, says Lisa Green ’93, professor of linguistics at UMass Amherst.

The term originated in black social media and took off with the Black Lives Matter movement to mean “be socially conscious or be aware of what goes on in the community.”  

“Stay woke is now used when someone makes an astute comment about just about anything,” says Green, the founding director of the campus’s Center for the Study of African American Language. 

“Twitter gives us real, live data about the way people actually talk,” she says. “It’s exciting for linguists because we know all languages change, but now we can actually see change in progress and map it geographically.”

Green recently collaborated with Brendan O’Connor, assistant professor at the College of Information and Computer Sciences, and computer science doctoral student Su Lin Wang Blodgett on a case study of dialect in Twitter conversations among African Americans. They collected a whopping  59 million tweets from 2.8 million users, including 830,000 tweets aligned with Twitter users in African American English-speaking neighborhoods.

Researchers will use this trove of tweets not only to study language, but also to teach computers to recognize African American English. In the past, computer scientists fed machines standard English through text from the Wall Street Journal and other conventional sources. The goal of the UMass project was to ensure that the computer can take in and analyze data from all segments of the population, no matter who they are and where they live, explains Green.

Twitter will be especially helpful for those linguists who research words and sounds. For instance, you might study the use and spread of the term talmbout for “talking about,” which demonstrates the natural language process of how the ng in “talking” changes to an m before the b sound in “bout,” allowing for smoother pronunciation. You might also study how and where “sure” became sholl, “love” became luh, and “even” was streamlined to een on Twitter.

“I had to be convinced that Twitter was a place to take linguistics seriously,” says Green. “Tweets have their drawbacks as data: They are very casual. They are susceptible to appropriation by people trying to sound cool, and the 140- character limit is not natural. But I have found that Twitter has potential to teach us a tremendous amount.”