Facebook ‘Likes’ reveal more about users than thought

Using a dataset of more than 58,000 U.S. Facebook users, University of Cambridge researchers predicted race, age, IQ, sexuality, personality, substance use and political views using Likes alone, the USA Today reported.

If a user “Likes” lots of people, places and things on Facebook, he or she may get rewarded with discounts and special offers. But new research shows that these public Likes reveal more about you than you may think.


Using a dataset of more than 58,000 Facebook users in the USA collected between 2007 and 2012, researchers at the University of Cambridge in the United Kingdom were able to accurately predict certain qualities and traits, such as race, age, IQ, sexuality, personality, substance use and political views using Facebook Likes alone.


The Likes include photos, friends' status updates, Facebook pages of products, sports, musicians, books, restaurants or popular websites.


"Likes represent a very generic class of digital records, similar to Web search queries, Web browsing histories, and credit card purchases," says the study in Proceedings of the National Academy of Sciences.


The participants gave researchers access to their Facebook pages and they completed a variety of online tests, including personality and IQ. Their Likes were fed into algorithms and researchers created statistical models that were able to predict the personal details using Facebook Likes alone. Results were corroborated with information from the Facebook profiles and personality tests.


"Each person, on average, liked 170 things," said psychologist Michal Kosinski, the study's lead author. "Some liked only one thing and there were people who liked thousands of things. We removed those. We looked at people who liked between one and 700 different things."


Sam Gosling, a psychologist at the University of Texas at Austin, has called it a "landmark study" because it illustrates "how things are no longer ephemeral." He has been studying Facebook behavior since 2006, and has seen this new study.


"You 'Like' something. You leave a comment on somebody's wall. They are now recorded in a way that machines can calibrate and measure them with great accuracy," he said. "Together, they add up to substantially more information from which you can make quite reasonably accurate predictions."