Is Twitter changing the English language?

Computer scientists have studied Twitter and noted clear linguistic differences between the language of men's and women's tweets. Tyler Schnoebelen of Stanford's PhD linguistics program, studied about 9 million tweets from English-speakers in the United States in an effort to understand the way we talk to each other. Schnoebelen and his coworkers were able to determine the gender of the creator of any given tweet with 88 percent accuracy just by noting the word choice of the tweeter.

Women are alleged to use more pronouns in their tweets. They also tend to be more emotional in their language using words such as “sad,” “love,” and “glad” in addition to using other online abbreviations such as “lol” and “omg.” Men, however, use standard dictionary words, numbers, proper nouns (especially those of sports teams) and taboo words more often than women.

Even Boston College has its own kind of lingo. Looking through a string of tweets from “Chestnut Hill, MA” one might find a series of tweets with #modlife or #BClookaway and maybe a #macprobz. We see accounts like our personal favorite here or a seasonal Twitpic. So the next time you hear someone say "I'd tweet that," you will know the complex linguistic study behind that comment.

Photo courtesy of Juan Andraca Sanchez/Wikimedia Commons

Twitter can also give us valuable insight into how we communicate with each other. A study by computer scientist Jacob Eisenstein—of the Georgia Institute of Technology in Atlanta—and his co-workers Brendan O’Connor, Noah Smith and Eric Xing—of Carnegie Mellon University in Pittsburgh—reveals how Twitter can develop language.

Eisenstein and his colleagues went through about “40 million messages from around 400,000 individuals between June 2009 and May 2011 that could be tied to a particular geographical location in the U.S. because of the smartphone metadata optionally included with the message,” according to a recent BBC article. Essentially, they were able to use phone signals to link tweets with the location from which they came.

Then they gave each area a “Metropolitan Statistical Area” (MSAs), which are “urban areas that typically represent a single city.” Next, they analyzed their results to figure out how these urban centers develop and influence each other based on their dissemination of language. They have tracked how phrases such as “bruh” or emoticons like “-__-“ become popular, resulting in a map of the USA that shows how phrases spread between centers and in what direction their influence is.

 

School, major and year: A&S, English major and French minor, 2015
Hometown: Bethesda, Maryland
Favorite Beyonce lyric: "A diva is a female version of a hustla"

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