In comparison, Global Positioning System have an average success rate for correctly diagnosing depression of 42%.
About half of the people in the study had been diagnosed with depression in the past three years.
Another key finding was that the depressed volunteers were more likely to post photos with faces - but these photos had fewer faces on average than the healthy people's Instagram feeds - a sign that perhaps depressed users interact with fewer people.
There have been other studies which have examined whether social media can display whether the user is in fact depressed.
Non-depressed people who use Instagram tended to post pictures which were warm and sunny.
'In other words, people suffering from depression were more likely to favour a filter that literally drained all the colour out the images they wanted to share, ' said the scientists.
Of the 166 people and 43,950 posts studied, it was also noted that depression was consistent with fewer posts.
"Pixel analysis of the photos in our dataset revealed that depressed individuals in our sample had the tendency to post photos that were, on average, bluer, darker, and grayer than those posted by healthy individuals."Читайте также: Northwestern professor and Oxford University employee wanted for murder
The study, published Tuesday in the journal EPJ Data Science, analyzed almost 44,000 Instagram photos from 166 volunteers, who also shared their mental health history. 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.
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 investigators then evaluated the photos using software programmed to look for known visual signs of depression. "One avenue for future research might integrate textual analysis of Instagram posts' comments, captions, and tags", the researchers concluded.
The methodology used meant that people with depression were correctly identified 70 percent of the time.
And using these factors, they were able to nearly double the likelihood of correctly diagnosing a patient with the technology, compared to a doctor in a consultation.
Danforth points out that while their research holds promise, the technology is still far from ideal.
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.
"We were looking for subtle patterns associated with depression, and that required sifting through a lot of data to be confident about what we were seeing", Reece said. The study was published online at EPJ Data Science.При любом использовании материалов сайта и дочерних проектов, гиперссылка на обязательна.
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