MONDAY, March 11 (HealthDay News) -- It's relatively easy to learn a lot about Facebook users -- from their political views and gender to their intelligence, race and sexual orientation -- by following their clicks, new British research reports.
Just clicking that you "like" something on Facebook leaves a virtual but lasting fingerprint of who you are, information that can be gathered and analyzed by marketers, credit agencies, companies, potential employers, politicians or the government, the researchers said.
Facebook "likes" and other digital records, such as Google browsing histories, are easily retrievable and can be used to create an accurate and revealing portrait of a person, said Michal Kosinski, lead study author and operations director of the Psychometrics Center at the University of Cambridge in England.
"I can tell you with confidence that I can predict who you are without you telling me anything at all, just from your Facebook 'likes,'" he added.
Clicking "like" on Facebook postings allows users to publicly express their positive association with online content, such as Facebook pages of restaurants, products, photos, quotes, musicians, sports figures, actors, organizations and movies.
Most people are unaware they are leaving a highly personal information trail, Kosinski said. Unlike data that most people guard carefully -- such as medical history or financial information -- "liking" something on Facebook seems casual and relatively unimportant to the user. What's surprising is that sensitive inferences can be drawn by organizations from seemingly non-sensitive data, he said.
Sophisticated data-gathering operations can analyze just about any information someone shares, said Lillie Coney, associate director of the Electronic Privacy Information Center, a public interest research organization in Washington, D.C.
"The biggest problem for consumers is that they don't know when they click to think three or four steps ahead about how that information could potentially be used," explained Coney, who was not involved with the research.
The study, published March 11 in the journal PNAS, tapped data from "myPersonality," a popular Facebook app that provides users with online tests about their personality, intelligence, emotional stability and life satisfaction. Apps are easy-to-use web applications.
Among all the users of myPersonality, about 58,000 agreed to give the researchers access to their Facebook profile and social network data, including tests they took using myPersonality.
The researchers developed a mathematical model and correlated what they learned just by assessing the participants' "liking" behavior to what the researchers knew about the participants from their psychological tests and profiles.
Based just on Facebook "likes," the research model predicted:
Gender, 93 percent of the time
Race, (white versus black) with 95 percent accuracy
Sexual orientation, (gay 88 percent of the time, and lesbian 75 percent of the time)
Drug use, with 65 percent accuracy
Political affiliation (Democrat vs. Republican), 85 percent of the time
Religion, (Christian vs. Muslim) with 82 percent accuracy
Relationship status, (single or with someone) 67 percent of the time
The authors also found that the research model was almost as accurate as a short personality test would be in predicting the Facebook users' degree of openness to new experiences.
The critical aspect of the research model was that it amassed large amounts of seemingly innocuous information, such as favorite music or television shows, love of animals or interest in friends' photos, to pinpoint a participant's distinct characteristics, Kosinski said.
Coney said data brokers mine browsing histories and social media sites to link a wide range of information to individuals, and sell their assessments to potential employers, politicians and others.
"Somebody will pay to use this data; the accumulated 'likes' are something people can sell," Coney said. "And, unfortunately, nobody is sending you notice that somebody is using this information."
Kosinski said psychological assessment models like the one he created could be used to potentially mine data from millions of Facebook users worldwide.
Kosinksi, who said he enjoys using Facebook and other online resources, urges consumers to be careful. He added, "People should be aware that whatever they do online can be used to infer traits and personality aspects way beyond what they believe it can be used for. [Our research] shows this can happen."
He said he hopes his research will start a discussion that leads policy makers and consumers to modify the technology so users have control over the data they create.
His study received funding from Microsoft Research, where he works as a consultant, and the Boeing Corporation.
Learn more about privacy issues in the information age from the Electronic Privacy Information Center.
SOURCE: Michal Kosinski, operations director, Psychometrics Center, University of Cambridge, and research consultant, Microsoft Research, Cambridge, England; Lillie Coney, associate director, Electronic Privacy Information Center, Washington, D.C.; March 11, 2013, PNAS