News

Language in Facebook posts could help spot health issues, study claims

New research suggests analysing frequent use of certain words on social media could help predict the diagnosis of some diseases.
New research suggests analysing frequent use of certain words on social media could help predict the diagnosis of some diseases. New research suggests analysing frequent use of certain words on social media could help predict the diagnosis of some diseases.

The language used in Facebook posts can be used to identify some medical condition, new research has claimed.

A new study by researchers from the University of Pennsylvania School of Medicine and Stony Brook University in the US suggests that analysing the content of posts to the social network could help spot signs of conditions such as diabetes, anxiety, depression and psychosis.

Analysing the language in Facebook posts from around 1,000 test patients, the researchers said it could be used to gain an insight into a person’s lifestyle choices and how they were feeling, which could also help with any potential treatment.

Lead author Dr Raina Merchant said: “This work is early, but our hope is that the insights gleaned from these posts could be used to better inform patients and providers about their health.

(Yui Mok/PA)
(Yui Mok/PA) (Yui Mok/PA)

“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.”

The researchers used an automated data collection technique to analyse the entire Facebook posting history of those who agreed to take part and to share their data. Participants also agreed to have electronic medical records linked to their profiles.

Three different models were then built to asses the data – one which focused on the Facebook data only, one which used demographics such as age and sex and a third which combined both datasets.

Looking into 21 different conditions, the researchers claim that all 21 were predictable from Facebook data alone.

The regular use of words such as “drink” or “bottle” could be used to predict alcohol abuse, while the use of hostile language was found to be an indicator of drug abuse and psychoses, the researchers said.

It follows a previous study carried out last year by some of the same team which suggested that social media posts could help predict a diagnosis of depression.

Those behind the latest study said it was difficult to predict how widespread an opt-in version of the system for patients could be, but Dr Merchant said would it “could be valuable” for those who use social media on a regular basis.

“For instance, if someone is trying to lose weight and needs help understanding their food choices and exercise regimens, having a healthcare provider review their social media record might give them more insight into their usual patterns in order to help improve them,” she said.

Dr Merchant is due to lead a trial later this year which will ask patients to directly share their social media content with their health care provider, which the researchers say will offer insight into how willing patients are to use their online posts as part of healthcare.