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Do your Facebook posts have God references? You are 15 times more likely to get diabetes

​​​Some of the Facebook data that was found to be more predictive than demographic data seemed intuitive. ​
Some of the Facebook data that was found to be more predictive than demographic data seemed intuitive.
WASHINGTON: Your Facebook posts may help identify conditions such as diabetes, anxiety, depression and psychosis, say scientists who suggests that language on social media posts with patient consent could be monitored just like physical symptoms.

Using an automated data collection technique, the researchers from University of Pennsylvania and Stony Brook University in the US analysed the entire Facebook post history of nearly 1,000 patients who agreed to have their electronic medical record data linked to their profiles.

The researchers then built three models to analyse their predictive power for the patients: one model only analysing the Facebook post language, another that used demographics such as age and sex, and the last that combined the two datasets.

Looking into 21 different conditions, researchers found that all 21 were predictable from Facebook alone. In fact, 10 of the conditions were better predicted through the use Facebook data instead of demographic information.

"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," said Raina Merchant, an associate professor at University of Pennsylvania.

"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," Merchant said.

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While being active, staying hydrated, and checking blood glucose levels can work wonders, it is important to stick to a dietary plan that will ward off diabetes in the long run. A recent study showed that antioxidant-rich walnuts can nearly halve the risk of developing Type-2 diabetes. For patients, the ideal diabetic diet plan would be to have 1200-1600 calories per day. It is recommended that diabetics should eat good carbs, fats, and healthy proteins, but in small portions. Doctors and dieticians share ultimate list of foods you must consume to stay healthy. Also read: The comprehensive diabetes guide
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Some of the Facebook data that was found to be more predictive than demographic data seemed intuitive.

For example, "drink" and "bottle" were shown to be more predictive of alcohol abuse. However, others were not as easy.

For example, the people that most often mentioned religious language like "God" or "pray" in their posts were 15 times more likely to have diabetes than those who used these terms the least.

Additionally, words expressing hostility -- like "dumb" and some expletives -- served as indicators of drug abuse and psychoses.

"Our digital language captures powerful aspects of our lives that are likely quite different from what is captured through traditional medical data," said Andrew Schwartz, an assistant professor at Stony Brook University.

Analysis of Facebook posts could predict a diagnosis of depression as much as three months earlier than a diagnosis in the clinic.​
Analysis of Facebook posts could predict a diagnosis of depression as much as three months earlier than a diagnosis in the clinic.

"Many studies have now shown a link between language patterns and specific disease, such as language predictive of depression or language that gives insights into whether someone is living with cancer," said Schwartz.

"However, by looking across many edical conditions, we get a view of how conditions relate to each other, which can enable new applications of AI for medicine," he said.

Last year, many members of this research team were able to show that analysis of Facebook posts could predict a diagnosis of depression as much as three months earlier than a diagnosis in the clinic.

This work builds on the study and shows that there may be potential for developing an opt-in system for patients that could analyse their social media posts and provide extra information for clinicians to refine care delivery.

Merchant said that it is tough to predict how widespread such a system would be, but it "could be valuable" for patients who use social media frequently.

"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," Merchant said.

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It seems counter intuitive – after all, social media helps you share your opinions and speak to a larger audience. But thanks to rampant identity theft and online stalking, there is a solid argument to be made to target your social posts instead of keeping them public. Karan Bajaj shows you how.
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