gpolit.com
gpolit.com December 13, 2017


Picture of Mental Health? What Your Instagram Photos Reveal About You

09 August 2017, 12:26 | Darrell Baldwin

Image Shutterstock KatePh

Image Shutterstock  KatePh

This method of rating the photos was far less reliable than a general practitioner's success rate of unassisted diagnosis, according to the study. People who aren't depressed, on the other hand, preferred the Valencia filter, which brightens the image. Half of the participants had been diagnosed with depression within the past three years.

"Depressed individuals in our study posted photos that were bluer, darker and grayer, compared to the posts of healthy participants", Reece said.

Depression is also characterized by reduced or avoidant social engagement.

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.

When the researchers analyzed the almost 44,000 images, they found that posts from users who had a diagnosis of depression were likely to be bluer, grayer and darker than posts from users without the condition.

Those who are depressed typically have darker photos, with blue and grey hues.

We all know that social media can have a negative effect on our mental health and self esteem - seeing endless ideal Instagram snaps of slim models with tanned limbs in exotic locations can often lead anxiety, self-worth and self-confidence issues.

The pics will tend to be darker, greyer and, well, "bluer", according to scientists.

The program wound up accurately assessing depression in Instagram users 70 percent of the time, the findings showed. The volunteers provided the researchers with information about past diagnoses of depression and responded to a questionnaire created to assess a person's level of depression. In a recently published study in the EPJ Data Science (via Mashable), researchers used machine learning to try and detect signs of depression from Instagram accounts.

Chris Danforth, who is also a co-director of the university's Computational Story Lab, commented that it is obvious for a person to have knowledge on a friend than computer; however, while flipping through the images, he might not be able to identify depression that efficiently.

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. Though more research is still needed, Danforth says this aspect is particularly encouraging. For example, the researchers said that they used a broad definition of depression, and looking at specific types of depression could lead to different results.

"This study is not yet a diagnostic test, not by a long shot", he said.

More than 500 participants initially were recruited for the study, the researchers noted, but many dropped out because they would not consent to sharing their social media data.



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