A new study finds that the language used in a participant’s Facebook posts is able to predict up to 21 medical conditions.
Researchers from Penn Medicine and Stony Brook University analyzed the Facebook statuses of 999 participants whose posts were more than 500 words — amounting to 949,530 posts on the social network. From there, scientists were able to predict 21 medical conditions — from pregnancy to skin issues — from the Facebook users’ updates.
“In what we believe to be the first report linking [EHR] data with social media data from consenting patients, we identified that patients’ Facebook status updates can predict many health conditions, suggesting opportunities to use social media data to determine disease onset or exacerbation and to conduct social media-based health interventions,” the authors write in their report published in the peer-reviewed journal PLOS One.
“People’s personality, mental state, and health behaviors are all reflected in their social media and all have tremendous impact on health,” authors of the study wrote. Facebook statuses were “particularly effective at predicting diabetes and mental health conditions including anxiety, depression and psychoses.”
According to the study, Facebook statuses were significantly better at predicting cases of diabetes, pregnancy, anxiety, psychoses, chronic pulmonary disease, STDs, drug abuse, collagen vascular diseases, coagulopathy (a blood-clotting disorder), and alcohol abuse.
The team of researchers used a total of 949,530 Facebook status updates across 999 participants. In order for a participant to be included, they had to have at least 500 words of status updates over the course of a two-year window.
“As social media posts are often about someone’s lifestyle choices and experiences or how they’re feeling, this information could provide additional information about disease management and exacerbation,” says Dr. Raina Merchant, director of Penn Medicine’s Center for Digital Health.
Researchers say future studies could compare the health-related information disclosed by users of different demographic populations and on other social media platforms.