Using Facebook to predict depression
17 October, 2018
New research uses over half a million Facebook status updates to predict depression diagnoses in people at risk.
Depression is one of the most widespread mental health problems in the United States, with over 16 million adults having experienced at least one major depressive episode in their lifetimes.
Worldwide, the World Health Organization (WHO) estimate that unipolar depressive disorders will be "the leading cause of the global burden of disease" by 2030.
Currently, however, the condition remains underdiagnosed, particularly among young people and men.
New research aims to help create better screening and diagnostic tools for depression by using the information provided by social media.
Researchers, jointly led by Johannes Eichstaedt, founding research scientist at the World Well-Being Project (WWBP) in Philadelphia, PA, and H. Andrew Schwartz, a principal investigator of the WWBP, used an algorithm to analyze social media data from consenting users and picked out linguistic cues that might predict depression.
The team published their findings in the journal Proceedings of the National Academy of Sciences. Johannes Eichstaedt is the first author of the paper.
Analyzing half a million Facebook posts
Eichstaedt and colleagues analyzed data from almost 1,200 people who agreed to provide their Facebook status updates and their electronic medical records. Of these participants, only 114 had a history of depression.
Study co-author Raina Merchant says, "For this project, all individuals [have] consented, no data is collected from their network, the data is anonymized, and the strictest levels of privacy and security are adhered to."
Then, for every person who had received a diagnosis of depression in their lives, the researchers matched another five controls who had not. In this way, the researchers matched 683 people.
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