PEOPLE WHO ARE sad are often said to be feeling blue, but colour may not just be a euphemism.
A new study from the University of Vermont suggests that depression can be signalled in social media picture choices.
The research showed that computers, applying machine learning, can successfully detect depressed people from clues in their Instagram photos. The computer’s detection rate of 70% is more reliable than the 42% success rate of general-practice doctors diagnosing depression in-person.
“This points toward a new method for early screening of depression and other emerging mental illnesses,” says Chris Danforth, a professor at the University of Vermont who co-led the new study with Andrew Reece of Harvard University.
“This algorithm can sometimes detect depression before a clinical diagnosis is made.”
They then analysed these photos, using insights from well-established psychology research, about people’s preferences for brightness, color, and shading.
“Pixel analysis of the photos in our dataset revealed that depressed individuals in our sample tended to post photos that were, on average, bluer, darker, and grayer than those posted by healthy individuals,” Danforth and Reese write in a blog post to accompany their new study.
They also found that healthy individuals chose Instagram filters, like Valencia, that gave their photos a warmer brighter tone. Among depressed people the most popular filter was Inkwell, making the photo black-and-white.
“In other words, people suffering from depression were more likely to favour a filter that literally drained all the color out of the images they wanted to share,” the scientists write.
Faces in photos also turned out to provide signals about depression. The researchers found that depressed people were more likely than healthy people to post a photo with people’s faces — but these photos had fewer faces on average than the healthy people’s Instagram feeds.
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