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 of Facebook data instead of demographic information.
A similar report published by Eurasia Review notes that 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 weren’t 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 the study’s senior author Andrew Schwartz, PhD, a visiting assistant professor at Penn in Computer and Information Science, and an assistant professor of Computer Science at Stony Brook University. “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. However, by looking across many medical conditions, we get a view of how conditions relate to each other, which can enable new applications of AI for medicine.”
Last year, many members of this research team were able to show that an 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 that study and shows that there may be potential for developing an opt-in system for patients that could analyze their social media posts and provide extra information for clinicians to refine care delivery. Merchant said that it’s 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.
Later this year, Merchant will conduct a large trial in which patients will be asked to directly share social media content with their health care provider. This will provide a look into whether managing this data and applying it is feasible, as well as how many patients would actually agree to their accounts being used to supplement active care.
“One challenge with this is that there is so much data and we, as providers, aren’t trained to interpret it ourselves — or make clinical decisions based on it,” Merchant explained. “To address this, we will explore how to condense and summarize social media data.”
However, the findings also raise several critical questions regarding privacy and data protection. Progressive data protection regulations such as the GDPR alleviate those concerns to some extent, but they may not fully prevent the technology from being used in a way that is potentially harmful to people. Job candidates might feel the pressure to check a box saying they agree to their data being processed, even though they consider it invasive.
It is therefore critical that businesses adhere to ethical principles and carefully consider both the potential costs and benefits before implementing income predictions from digital footprints.
Image Courtesy: The Verge, British GQ, The Daily
(DIDHITI GHOSH is an India Columnist at La Agencia Mundial de Prensa, USA, and is the Bureau Chief of Indian Observer Post based in Kolkata. E-mail: didhiti.24@gmail.com | LinkedIn: https://bit.ly/2H6gNAv).