Computer software created to scan photos for these hidden signals accurately diagnosed people with depression seven out of 10 times, said lead researcher Andrew Reece. That could support - although the authors emphasize this is untested - a "sad-selfie hypothesis", in that depressed people may post more photos of only themselves. Those experiencing some sort of depression tended to opt for darker colors in their Instagram photos, whereas those who weren't gravitated toward more vivid colors.
Depressed people more frequently used blue, grey, and dark tones, and generally avoided filters, but when they did use them, they predominantly preferred the black-and-white Inkwell option. Being able to spot mental illnesses more easily is the first step to connecting people with the help they need.
As another component of the study, Danforth and Reece had a different set of volunteers identify whether the Instagram posts were made by depressed or healthy individuals. Using a photo filter was less common among the individuals with depression diagnoses than among those without it.
The research is only a proof of concept right now and it can't be said for sure whether it can have a similar application on a larger scale. "Whether or not it would translate to average person's Instagram feed, we don't know", Professor Danforth said.
Dr Christopher Danforth, one of the researchers, said: "With an increasing share of our social interactions happening online, the potential for algorithmic identification of early-warning signs for a host of mental and physical illnesses is enormous".
A key finding was that the computer was able to detect signs of a person's depression in photos posted before the problem was diagnosed.
The results of the study also align with what mental health professionals have observed in the past, Danforth said. Participants were selected so that roughly half in the study had experienced episodes of depression. They rated 20 random photos chosen from the almost 44,000 included in the study.
Almost 300 million people worldwide are affected by depression.
Danforth points out that while their research holds promise, the technology is still far from flawless. Especially when they may be unaware about what's going on or hesitant to reach out on their own. "Because maybe there's something going on that even the individual doesn't recognize about their behavior".
There have been other studies which have examined whether social media can display whether the user is in fact depressed.
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