Depression Can Be Detected in Your Instagram Photos
Depression cannot only be detected by a clinical diagnosis but also through social media images, according to a new study. The algorithm is even more reliable than your GP!
The study asserts that photos in social media, particularly in Instagram, can track traces of depression among users. One might question how is this possible?
Researchers from Vermont University just completed an amazing social media study on this subject.
According to the researchers, 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.
Another key finding of the study also shows the ability of the algorithm to detect depression before a clinical diagnosis is made.
This new discovery was reported by a team of researchers composed of Chris Danforth, a professor at the University of Vermont and Andrew Reece from Harvard University
Danforth said, “This points toward a new method for early screening of depression and other emerging mental illnesses.”
The team’s results were published August 8 in a leading data-science journal EPJ Data Science.
Filters in Instagram and Facebook
The researchers invited 166 people to be respondents in the study and collected 43,950 photos from them. All of the respondents reported having been clinically depressed in the last three years.
The photos were analyzed by using insights from well-established psychology research, about people’s preferences for brightness, color, and shading.
The results show a correlation between the use of filters in the photos posted online and depression.
According to the researchers, healthy participants 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 favor a filter that literally drained all the color out of the images they wanted to share,” the scientists write.
In addition, faces in photos also turned out to provide signals about depression. This means that depressed people have fewer faces found in the photo compared to healthy individuals, but have more tendency to do ‘selfie’ shots.
“Fewer faces may be an oblique indicator that depressed users interact in smaller settings,” Danforth and Reece noted.
The Wonders of Computational Algorithm
To distinguish between Instagram posts made by depressed people versus healthy, the researchers used a statistical computer model. The method is more effective and accurate than human ratings when analyzing photos.
Interestingly, use of the computational algorithm was able to detect signs of depression before a person’s clinical diagnosis.
“This could help you get to a doctor sooner,” Danforth says. “Or, imagine that you can go to a doctor and push a button to let an algorithm read your social media history as part of the exam.”
Based on the efficacy of the algorithm, the researchers saw great benefits in the application for helping people early in the onset of mental illness, avoid false diagnoses. It may also offer a new lower-cost screening for mental health services, especially for those who might not otherwise have access to a trained expert, like a psychiatrist.