More first-person pronouns, and mentioning loneliness are both warning signs.
Sometimes it’s easy to detect when a friend is depressed. They withdraw, talk negatively and don’t enjoy the activities they used to. They may seem a bit lost.
At other times, it comes as a surprise. That person who is the life of the party and always on the go, turns out to be suffering the most.
It can be hard to feel that you could have done more. Thankfully, researchers from the University of Pennsylvania have discovered a new “tool” for detecting depression that could help.
Scientists developed an algorithm that can accurately predict a person’s impending blues. By analyzing the words found in someone’s posts, it was possible to detect what might be going on in their mind.
Interestingly, words like “tears” and “feelings,” and an increased use of first-person pronouns like “I” and “me” showed that someone was going downhill. Mentions of hostility and loneliness also counted, (naturally).
“What people write in social media and online captures an aspect of life that’s very hard in medicine and research to access otherwise,” says H. Andrew Schwartz, the study’s senior author. “It’s a dimension that’s relatively untapped…Considering conditions such as depression, anxiety, and PTSD, for example, you find more signals in the way people express themselves digitally.”
Social media contains markers akin to the human genome says researcher Johannes Eichstaedt. Depression changes people’s use of social media.
Of course, the study wasn’t foolproof, but it offers professionals hope that new ways of detecting problems might soon be available.
For more on the study, click here.
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