New Delhi: Social media platforms like Facebook and Instagram are widely popular among all age groups.
From the young to the old, people love sharing images on both platforms. For most people, it's a way of expressing themselves through the pictorials.
Many studies have previously churned out conflicting conclusions on whether these portals affect users' mental health, with some saying it causes depression and others saying it helps those suffering from it.
However, a new study has come forth which says that whether a user is suffering from depression or not can be deciphered just by looking at the images they share.
Scientists have developed a new computer programme that could diagnose depression from social media posts better than doctors.
The programme could identify depressed people correctly 70 percent of the time.
In comparison, previous research has shown that doctors can make a correct unassisted diagnosis of depression 42 percent of the time.
"Our analysis of user accounts from a popular social media app revealed that photos posted by people diagnosed with depression tended to be darker in colour, received more comments from the community, were more likely to contain faces and less likely to have a filter applied," said Christopher Danforth, from the University of Vermont in the US.
"When they did select a filter they were more likely to use the filter that converted colour images to black and white. People diagnosed with depression also posted at a higher frequency compared to non-depressed individuals," said Danforth.
"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," he said.
"Imagine an app you can install on your phone that pings your doctor for a check-up when your behaviour changes for the worse, potentially before you even realise there is a problem," he added.
The researchers used the computer programme to analyse 43,950 photos, following recruitment of 166 users of a popular social media app, including 71 people that had a clinical diagnosis of depression.
The programme scoured the photos for details that were associated with healthy and depressed individuals.
This information was then used to see if the programme could predict who would go on to be diagnosed with depression by only looking at photos that were posted before their diagnosis.
"Although we had a relatively small sample size, we were able to reliably observe differences in features of social media posts between depressed and non-depressed individuals," said Andrew Reece from Harvard University in the US.
"Importantly, we also demonstrate that the markers of depression can be observed in posts made prior to the person receiving a clinical diagnosis of depression," Reece said.
The research was published in the journal EPJ Data Science.
(With PTI inputs)
