It turns out your Instagram filter can be a surprisingly good indicator of whether or not you are depressed, and now computer scientists at Stony Brook University and the University of Pennsylvania have invented an algorithm that uses Facebook language to predict a user's diagnosis of depression. [...]
The algorithm, described in a paper published in Proceedings of the National Academy of Scientists, was built using 524,292 Facebook updates, some of which were from individuals who were later diagnosed with depression. Researchers singled out the words and phrases most frequently used and categorized them into 200 topics to identify so-called "depression-associated language markers". The language of the depressed group could then be compared to that of the control group to spot patterns between the two.[...]
Language markers associated with emotional, cognitive, and interpersonal processes (including hostility, loneliness, rumination, and sadness) could all help predict depression up to three months before an official diagnosis. As previous research has shown, the algorithm found that people with depression were more likely to use first-person singular pronouns like I, my, and me. They were also more likely to use words associated with depressed moods (tears, cry, pain), loneliness (miss, much, baby), hostility (hate, ugh, fuckin), anxiety (scared, upset, worry), and rumination (mind, alot).
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