Can social media posts reveal early signs of mental illness? A new machine learning model shows promising results.

What’s new: Researchers led by Michael Birnbaum at the Feinstein Institute for Medical Research and Raquel Norel at the IBM Watson Research Center developed a model that analyzes messages and images posted by Facebook users for indicators of psychological problems. Unlike earlier efforts to classify mental illness based on social media posts, which relied on subjects to report their condition, this one used actual diagnoses.

How it works: The authors collected millions of messages and images posted over 18 months by 223 volunteers. Some posters had been hospitalized with schizophrenia-spectrum disorders, some had been diagnosed with mood disorders like depression, and some had no mental health issues.

  • For text input, the authors labeled training examples using LIWC, which represents emotional tone, confidence, and authenticity. For images, they annotated measurements of hue, saturation, pixel density, and other factors.
  • They trained a random forest to classify messages from each group.

Results: The model identified people diagnosed with schizophrenia and mood disorders at a rate comparable to that of a standard 10-point questionnaire, according to Wired. The researchers found that individuals diagnosed as schizophrenic used “see,”  “hear,” and other words related to perception more often than the others. Those with mood disorders tended to post more blue-tinted pictures. Both groups also used more swear words and posted smaller photos.

Behind the news: Social media posts are a popular hunting ground for researchers aiming to gauge users’ mental states. Recent studies suggest that Reddit comments can indicate conditions like ADHD, anxiety, and bipolar disorder, and that Twitter users often telegraph their depression, postpartum mood disorder, suicidal ideation, and more.

Why it matters: This tool could help doctors catch mental illness early — especially in young adults, who tend to be both prolific users of social media and at higher risk of developing mental illness — and could provide valuable context for treatment.

We’re thinking: Useful though it might be in some cases, using natural language processing to scan social media posts for clues to a user’s mental state holds worrisome implications. Yet another reason social media companies must adopt stricter standards to protect privacy.


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