Now researchers believe that how often you post on social media could be an indicator to underlying, and potentially untreated, mental health issues.
According to the study, published by EPJ Data Science, researchers from Harvard University and the University of Vermont assessed just under 44,000 photos from 166 users - 71 of which had a history of depression.
The system used a variety of factors to make its decision, such as choice of color, the filters used, face detection, user comments, and how much one is engaged in their posts.
"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.
It could also spot signs of depression in images shared even before their illness was diagnosed by doctors, they said. People without depression preferred the Valencia filter, which gives photos a sun-kissed look, far more than depressed people did. By design, roughly half of our study participants reported having been clinically diagnosed with depression sometime in the last three years.
In the study, the researchers looked at the Instagram feeds of more than 160 volunteers, recruited from Amazon's Mechanical Turk, an online crowdsourcing platform. That could support - although the authors emphasize this is untested - a "sad-selfie hypothesis", in that depressed people may post more photos of only themselves.
Une inquiétante vidéo de Sinead O'Connor
Visiblement désespérée, la chanteuse irlandaise lance un appel à l'aide à travers une vidéo publiée sur sa page Facebook . L'appel au secours a déjà été vu plus de 700.000 fois. "Elle est entourée d'amour et reçoit la meilleure attention".
"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 greyer than those posted by healthy individuals", the researchers wrote in a blog post.
However, these photos had fewer faces on average than the healthy people's Instagram feeds which, the scientists say, corresponds to existing research linking depression to reduced social interaction. But when individuals with a depression diagnosis did use filters, many preferred to filter all the color out of their posts, opting for black-and-white filters such as "Inkwell".
Danforth said in a statement that while we tend to know our friends better than a computer could, "you might not, as a person casually flipping through Instagram, be as good at detecting depression as you think".
A key finding was that the computer was able to detect signs of a person's depression in photos posted before the problem was diagnosed.
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.
"This study is not yet a diagnostic test, not by a long shot", said Danforth, "but it is a proof of concept of a new way to help people".
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