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Grammar and spelling are minor matters on Twitter, Facebook, and Co. People want to sound authentic and show emotion, for example, by elongating words: “Yeesss!” An analysis of 100 billion tweets shows that such “pseudo-verbal” spellings are on the rise and developing a life of their own.
When speaking, there are many ways of expressing yourself other than through gestures and facial expressions. Sound and emphasis can also emphasize and change the meaning or show how the speaker feels. Lengthening individual words or vowels and consonants is a simple way to give what is being said a certain direction or simply more weight.
This turns a harmless “Goal!” into the enthusiastic exclamation we know from sports reporting: “Toooooor!”. It can also be used to signal danger: “Hiiiilfeeee!”, to add emphasis to what has been said: “Neiiiiin!” or to add an ironic undertone: “Aber siiiicher!” Originally, this form of distortion hardly ever occurred in written language, apart from literary texts or in comics, where dialogs are supposed to sound as realistic as possible.
“Pseudo-verbal” communication
Only in the past two decades have such oral language elements increasingly found their way into writing—digitalization is responsible for this. Instead of talking to each other directly or on the phone, people now communicate much more frequently in writing than in the past, by email, text message, and via social media—this is often reflected in a “pseudo-verbal” form that is not only used by young people in the digital space today. Emojis, for example, are used to replace a smile or a wink in conversation. The language itself also bears the typical hallmarks of orality. Sentences are often incomplete, based on dialect, and, similar to speech, words are stretched to emphasize a certain meaning or express feelings.
Researchers led by Tylor Gray from the University of Vermont have now used a specially developed method to statistically investigate which words are stretched, how often they are used, and how their use changes. For their study, which has just been published in “PLOS ONE,” they analyzed ten percent of all Twitter data from September 2008 to December 2016—more than 100 billion tweets. Most were written in English, but other languages, such as Spanish and Portuguese, also appeared in the data set.
“Hahahaha” and ”Yeessss!”
During the systematic search, the team identified thousands of stretchable words—mostly words that convey feelings or moods. Onomatopoeic words such as “Hahahahaha” are stretched particularly often, but affirmative particles such as “Yeeessss!”, salutations such as “Duuuude” or adjectives such as “awesssssommmmmeeeeee” are also frequently elongated.
According to the researchers, the analyzed data also shows how the use of elongated words has changed over the course of eight years. Initially, they referred more or less directly to the pronunciation; i.e., oral variants were simply imitated in writing. Over time, however, the written elongation developed a kind of life of its own. This can be seen, for example, in which vowels or consonants are multiplied. Whereas in the early years, there were mostly theoretically audible elongations, such as in “Yes!”, by the end of the analysis period, there were increasingly frequent elongations that could not be pronounced at all, such as in “Please” or “Help”. In general, the final letter is increasingly multiplied.
Independent linguistic feature
This is a sign that the initial onomatopoeic elongation has developed into an independent visual stimulus for the researchers. Stretched words are very visible. Some tweets even consist of just a single elongated word. Sometimes, every letter is even doubled or multiplied to attract more attention.
With the help of the method developed by the researchers, it will be easier in the future to search specifically for elongated words—this is not so easy with conventional search algorithms. The authors write that this could help to clarify linguistic questions relating to how they are used communicatively, for example, whether there are differences between the various electronic channels with and without character restrictions. Language processing programs could also benefit from the method. They currently still have many problems when it comes to “understanding” non-standardized language in social media. The new method could also help with spell-checking.
- source: orf.at/picture: Image by Gino Crescoli from Pixabay
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