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Your Instagram feed and the filters you use can reveal if you’re depressed, researchers say

PUBLISHED : Tuesday, 23 August, 2016, 12:36pm
UPDATED : Tuesday, 23 August, 2016, 9:36pm

If you’ve ever paused to reflect on the moody, filtered shots of a friend’s Instagram feed and wondered if you should reach out, a new study may confirm your worries.

Researchers Andrew Reece of Harvard University and Chris Danforth of the University of Vermont collected survey information and Instagram photos from 166 volunteers recruited through Amazon’s Mechanical Turk, which pays people small amounts to perform tasks.

Each participant was asked to complete a standardised clinical depression survey to assess depression level, answer demographic questions and share information about their use of social media including their Instagram usernames. The researchers then analysed the photos for quantitative measures of colors, brightness and faces, as well more subjective assessments of happiness, sadness, likeability and “interestingness.”

The study is the latest in a body of research that looks at how changes in your psychology are reflected in social media.

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A team from Northwestern University Feinberg School of Medicine examined how three aspects of movement in time and space which they dubbed “circadian movement,” “normalised entropy,” and “location variance” appear to correlate with symptoms of depression. Another study, out of Sweden, found that frequent cellphone use was associated with stress, sleep disturbances, and symptoms of depression among both young adult men and women.

Fewer faces [per photo] may be an oblique indicator that depressed users interact in smaller social settings
Researchers Andrew Reece and Chris Danforth

The key finding in the new study has to do with the curious relationship between your mood and color. It turned out increased hue, with decreased brightness and saturation, appeared to predict depression. Hue refers to the place on a 360-degree colour wheel, brightness from black to white, and saturation to what photographers call “colourfulness” or the intensity of a colour. In other words, people who are depressed had pictures that were “bluer, grayer and darker.”

Depressed participants in the study were also more likely to post more frequently and to post more photos with faces - and to apply more and different types of Instagram filters.

The most popular one for people who are depressed? Inkwell, which turns colour photos black and white. “Healthy” participants, people the study defined as not being depressed, tended to favour the Valencia filter which they said “lightens the tint of photos.”

This chart of filter usage by volunteers who are depressed vs. those who are not is striking.

One of the most fascinating findings has to do with faces. Researchers found that depressed users were more likely to post photos with faces. However, they had fewer faces in each photo.

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“Fewer faces may be an oblique indicator that depressed users interact in smaller social settings, which would be in accordance with research linking depression to reduced social interactivity,” Reece and Danforth wrote.

The study also involved asking volunteers (different ones) to rate the photos in terms of happiness, sadness, likability and interestingness. As might be expected, the photos from depressed participants’ feeds were more likely to be sad and less happy.

One important thing to note is that the researchers were able to detect these “depressive signals” as they called them in posts made even before the date of first diagnosis.

The researchers wrote that these findings “suggest new avenues for early screening and detection of mental illness.” It’s unclear how that would work. Would you one day give your clinician your Instagram username or would bots scan millions of Instagram feeds and somehow report back to you that you might be depressed?

Reece and Danforth’s work was released on arXiv, an open-access service run by Cornell University, which allows scientists to share research before it’s formally published based on the idea that it can accelerate the pace at which others can build on the knowledge.

That means it’s still methods that have not yet been officially independently reviewed or checked so you should take the findings with a grain of salt. There’s also the issue that the volunteers were crowd-sourced through Amazon Mechanical Turk which tends to attract those with a lot of free time on their hands rather than, say, people who put in 60-hour work weeks.