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Study

Researchers Determine Facebook Users’ Sexual Orientation with 75-88% Accuracy

C. Price

Written by: C. Price

C. Price

C. Price is part of DatingAdvice.com's content team. She writes advice articles, how-to guides, and studies — all relating to dating, relationships, love, sex, and more.

Edited by: Lillian Castro

Lillian Castro

Lillian Guevara-Castro brings more than 30 years of journalism experience to ensure DatingAdvice articles have been edited for overall clarity, accuracy, and reader engagement. She has worked at The Atlanta Journal and Constitution, The Gwinnett Daily News, and The Gainesville Sun covering lifestyle topics.

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How much do Facebook “Likes” reveal about a person?

Researchers at the University of Cambridge found they were able to determine a user’s sexual orientation, gender, intelligence quotient, political and religious beliefs, and substance use with 80% accuracy.

The study reviewed 55,814 user “Likes” and used this data to make startlingly accurate predictions about each user’s personality traits and personal orientations.

For example, researchers were able to determine each user’s sexual orientation with 75 to 88% accuracy, gender with 93% accuracy and relationship status with 65% accuracy.

“Researchers were able to determine sexual

orientation with 75-88 percent accuracy.”

Interestingly enough, researchers found it was easier to accurately predict male sexual orientation than female sexual orientation.

Researchers predicted political and religious affiliation with 82 to 85% accuracy and race with 95% accuracy.

The study ultimately notes this predictive power may hold true for a wide range of online activity tracking, not just Facebook “Likes.”

“Similarity between Facebook Likes and other widespread kinds of digital records, such as browsing histories, search queries or purchase histories, suggest that the potential to reveal users’ attributes is unlikely to be limited to Likes,” researchers said. “Moreover, the wide variety of attributes predicted in this study indicates that, given appropriate training data, it may be possible to reveal other attributes as well.”

Source: Pnas.org.

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