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Depressed people can be recognized by their language on the Internet
Depression has long become a widespread disease. As reported by the German Depression Aid Foundation, every fourth woman and eighth man will experience at least one depression in the course of their lives. But not everyone affected receives the help they need to defeat the disease. This is not least due to the fact that many people do not admit their illness or do not actively seek help. American researchers have now developed an algorithm that scans entries from social media, thereby filtering out those who either have depression or are at greater risk of developing it.
American researchers from the University of Pennsylvania and Stony Brook University drew on recent research that decoded a type of language code for depressed people. From this language code, the scientific team programmed an algorithm that scans entries in social networks such as Facebook and thus recognizes warning signals for individual users that a depression is present or is about to develop. The study results were recently published in the renowned journal "Proceedings of the National Academy of Science" (PNAS).
Detect depression before it develops
According to the German Depression Aid Foundation, around 5.3 million people in Germany are affected by depression. The newly developed algorithm could help accurately predict future depression before a medical diagnosis is made. In this way, more people could receive help, which in many cases is necessary to overcome a depressive illness.
The language of depression
Several studies have already confirmed that depressed people use a striking language. This is characterized by negative adjectives such as lonely, sad or unhappy as well as words such as tears, pain, feelings, loneliness and hostility. In addition, depressed people use the ego pronoun "me" more often, but far less second or third-party pronouns like you, he, she or it.
How social media can help diagnose depression
"What people write on social media captures an aspect of life that is difficult to access in medicine and research," says lead study author H. Andrew Schwartz in a press release on the study results. The research team plans to use this information as a disease marker to uncover depression, anxiety disorders and post-traumatic stress disorders.
Six years of research
Based on a six-year language analysis, the researchers developed a program that can recognize and predict depression among users of social media. “Depression seems to be quite demonstrable in this way, since people affected change the use of social media in a very specific way,” explains Schwartz. This would not be the case with a skin disease or diabetes.
Results similar to a screening test
The researchers analyzed the data from the social media of 1200 participants. 114 of them suffered from depression. The algorithm should now recognize depressed people independently. To do this, he scoured more than 500,000 entries. In fact, the program managed to detect depression with a reliability that was similar to that of common screening tests.
The language changes within months
As a check, the researchers evaluate entries from depressed people who were more than six months ago. In many cases, the algorithm could not detect any depression here, which indicates that the language has actually changed.
An unobtrusive depression test?
The scientist Johannes Eichstaedt from the University of Pennsylvania involved in the study sees long-term potential in the algorithm. It can be used as an unobtrusive depression test without having to answer uncomfortable questions. He hopes that one day this program will be integrated into the health system. (vb)