Scientists at Cambridge University report surprisingly accurate estimates of Facebook users' race, age, IQ, sexuality, personality, substance use and political views can be inferred from automated analysis of just their Facebook Likes.
That information is currently publicly available by default, they said, and can be used in the same way as Web search queries and browsing histories to reveal information about almost anyone who is regularly online.
More that 58,000 U.S. Facebook users volunteered their Likes, demographic profiles and psychometric testing results and gave consent to have profile information recorded for analysis by the researchers.
The Facebook Likes were fed into algorithms and corroborated with information from profiles and personality tests, the Cambridge scientists said.
The algorithms proved 88 percent accurate for determining male sexuality, they said, 95 percent accurate distinguishing African-American from Caucasian American and 85 percent accurate differentiating Republican from Democrat.
Christians and Muslims were correctly classified in 82 percent of cases, and good prediction accuracy was also achieved for relationship status and substance abuse, the study found.
While the results suggest the potential for personalized marketing, the researchers warned of the threats posed to users' privacy, saying many online consumers might feel such levels of digital exposure exceed acceptable limits.
"Similar predictions could be made from all manner of digital data, with this kind of secondary 'inference' made with remarkable accuracy -- statistically predicting sensitive information people might not want revealed," Michal Kosinski of Cambridge's Psychometric Center said.
"Given the variety of digital traces people leave behind, it's becoming increasingly difficult for individuals to control."