A new study analyzes social media posts to look for clues of mental illness. Analyzing photos pixel-by-pixel for color, metadata, and face detection, it then uses its observations to predict which users had depression and which didn’t. This interesting information came to us from Motherboard in their article, “People with Depression Tend to Post Darker Instagrams.”
The analysis was only on photos; it didn’t consider any related text, like captions or comments. The model correctly identified the people with depression 70 percent of the time—that’s better than the average primary care doctor, who correctly diagnose depression about 50 percent of the time.
On Instagram, the computer model identified a number of trends among users with depression. Their photos tended to be bluer, darker, and grayer, unfiltered, have more comments, and fewer likes. When they did use a filter, they preferred the black-and-white lens, while the control group greatly preferred warm and sunny.
This doesn’t mean the friend who posts all black-and-white Instagrams is definitely suffering from depression, but when taken in the context of the comprehensive data that is shared in social media every day, it could help give some clues about what’s going on beyond the lens.
Melody K. Smith
Sponsored by Data Harmony, a unit of Access Innovations, the world leader in indexing and making content findable.
