Feeling Blue? Social Media Colors Diagnose Depression More Accurately Than Doctors

The greater hue, lower saturation, and reduced brightness of the photo on the right are all indicative of depression when posted on social media. Chris Danforth 

A computer model can diagnose depression based on an image in a social media user's post with an accuracy of 70 percent. While imperfect, this easily exceeds the 42 percent success rate achieved by general practitioners when assessing someone in person. The finding could lead to frightening privacy intrusions, but could also increase the chance of people getting the help they need.

Professor Chris Danforth of the University of Vermont had 166 volunteers provide access to their Instagram accounts, with a total of 43,950 photographs. They also provided records of their mental health, with 71 participants having been diagnosed with depression in the previous three years. Images were analyzed for features, such as whether they included faces, the filters applied, and responses received.

Danforth tried several algorithms, drawing on research showing people’s preferences regarding color and brightness change when depressed. In EPJ Data Science he reported that the most successful algorithm proves there is a reason we talk about “feeling blue”.

"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 his co-author, Harvard graduate student Andrew Reece, write in a blog post discussing their work. Those who were depressed steered clear of Instagram filters that make images look warmer or lighter, preferring Inkwell, which turns color shots to black and white. "In other words, people suffering from depression were more likely to favor a filter that literally drained all the color out the images they wanted to share," the authors write.

Color was not the only distinguishing feature. People with depression posted more often, but used photographs with fewer people in them, which the authors speculate may reflect the reduced amounts of socializing. However, the authors also note that since the computer did not distinguish between selfies and photos of others, there may be a tendency for people who are suffering to not post pictures of themselves.

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