Instagram images may detect your mental health

Instagram images may detect your mental health

According to the research paper, the methodology was able to identify depression in people with 70 percent accuracy, which is greater than the average 50 percent accuracy of doctors while diagnosing depression. The control participants, who had no record of depression, used the bright filter "Valencia" most frequently. A little less than half of the participants had been diagnosed with depression within the past three years.

People with depression diagnoses were also more likely to post photos with people in them, but compared to other users, the posts had fewer people per photo, the researchers found.

Indeed, some of the photo features that the researchers identified "match common perceptions regarding the effects of depression on behavior", the authors noted.

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.

"Photos posted by people with depression tended to be darker in color, received more comments from the community, were more likely to contain faces and less likely to have a filter applied", study co-author and codirector of the University of Vermont's Computational Story Lab, Dr. Christopher Danforth said in a statement. The photos posted by individuals with depression diagnoses were more likely to be rated as sadder and less happy than those of users without. While the majority guessed correctly, the computer model analysis proved more accurate.

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We all know that social media can have a negative effect on our mental health and self esteem - seeing endless flawless Instagram snaps of slim models with tanned limbs in exotic locations can often lead anxiety, self-worth and self-confidence issues. Pixel analysis of the photos in our dataset revealed that depressed individuals in our sample tended to post photos that were, on average, bluer, darker, and grayer than those posted by healthy individuals. New research out of the University of Vermont and Harvard, using Amazon's Mechanical Turk to crowd source data, shows when a social media user is depressed it's revealed in the photos they post on Instagram. This algorithm does not even need any kind of clinical diagnosis before confirmation. Healthy participants tended to favor the "Valenica" filter, which makes the tint more vibrant.

In addition, much more research is needed before this type of technology could be used to diagnose mental health conditions. "But it is a proof of concept of a new way to help people", Danforth said.

"We have a lot of thinking to do about the morality of machines", he said.

EJP Data Science examined 166 people and 43,950 posts before making conclusions, though it claims the results are overwhelming.

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