Have you ever wondered how genuine that smile really is?
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If your intuition isn't stellar at gauging real versus fake smiles, this information might be of interest to you: Researchers at MIT have developed a computer algorithm to distinguish honest-to-goodness smiles from those simply trying to mask frustration.
Experiments conducted at MIT's Media Lab asked people to act out expressions of delight or frustration -- and webcams captured their reactions. Researchers then watched the participants either fill out an online form purposefully designed to cause frustration, or invited them to watch a video designed to draw out delight. The researchers captured and logged each smile.
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The results? According to Ehsan Hoque, graduate student in the Affective Computing Group of MIT's Media Lab and lead author of the paper documenting the research, when asked to feign frustration, an overwhelming majority of the subjects -- 90% -- didn't smile. Yet when it came time to fill out the form intentionally designed to be frustrating, the same percentage of people did smile to cope with the situation.
While still images of the photographs showed little difference between the frustrated smiles and the delighted smiles, the video analysis of the experiences eliciting those reactions revealed the nuances -- especially regarding the progression of the smiles. While the genuine, happy smiles built up gradually, feigned smiles appeared quickly but faded just as fast.
With the data accumulated from the experiment, the researchers then created the computer algorithm they say is more effective than humans at determining the sincere smiles.
"We humans can normally zoom out and try to interpret an expression, whereas a computer algorithm can utilize the nitty gritty details of a signal, which is much more enriching than just zooming out and looking at the high-level picture," Hoque said.
Indeed, when humans were asked to interpret the smiles, they were only 50% successful at accurately determining the real responses. The algorithm, on the other hand, was correct 92% of the time.
In addition to noting the timing of the smiles, the algorithm tracks the movements of different facial muscle groups, which also come into play when people smile. Phony smiles tend to be made with just the major muscles at the corners of the mouth. Real smiles, though, involve involuntary muscles that raise the cheeks and cause crinkles around the eyes.
And who might be able to benefit from the research? Just about anyone, says Hoque. Timing especially has much to do with how people interpret expressions. For example, he says, people perceived former British Prime Minister Gordan Brown as having a fake smile because of the unnatural timing of his grin. Similarly, when former presidential candidate Herman Cain came out with a campaign video that concluded with him displaying an incredibly slow-motion smile -- it took 9 seconds to appear -- it was widely parodied.
"Getting the timing right is very crucial if you want to be perceived as sincere and genuine with your smiles," Hoque says.
Although knowing how to create genuine smiles just might obviate the sincerity behind them -- if people do in fact take the time to appear happy when they really aren't -- Hoque says the goal of the research is "to help people with face-to-face communication."
That means that this information is especially important in areas like autism, since autistic people are generally taught that a smile means someone is happy. Potentially, the research could help train autistic people and others who have difficulty interpreting expressions how to more accurately gauge the expressions they see.
Not only that, but the information could also be useful to marketers in assessing customer satisfaction. As Hoque says, "The underlying meaning behind the smile is crucial."
Would you be interested in a computer algorithm to figure out real versus fake smiles? Let us know in the comments.
This story originally published on Mashable here.