Privacy at risk on Facebook and Twitter, even if one has no account, says study

A new study now finds that privacy on social media is controlled by people around the user.

While individual choice has long been considered to be the basis of online privacy, the new study presents evidence that is otherwise.

The study was published January 21 in the journal Nature Human Behavior.

The study saw scientists from the University of Vermont and the University of Adelaide gather more than thirty million public posts on Twitter from 13,905 users.

The information that was made available through the data allowed researchers to decipher that Twitter messages from 8 or 9 of a person's contacts make it possible to predict that person's later tweets as accurately as if they were viewing the person's own Twitter feed.

The study further revealed that if a person leaves social media or has never been a part of one, the online posts and words of their friends still provide about 95 per cent of the "potential predictive accuracy."

On the other hand, when one signs up for Facebook or any other social media platform, the person inadvertently gives up information, not only about themselves, but also about their friends, said lead author James Bagrow, from the University of Vermont.

Bagrow's research raises profound questions about the fundamental nature of privacy, and how, in a highly networked society, a person's choices and identity are embedded in that network.

The study finds that, at least in theory, a company, government or other institution, can accurately profile a person, from what their friends have posted, even if they have never been on social media or have deleted their account.

Lewis Mitchell, co-author on the study added, "There's no place to hide in a social network."

While information being posted on social media has become a powerful platform in protest movements, elections and the rise and fall of commercial brands, scientists, till now have not know if there is a fundamental limit to how much predictability is contained within this data.

In the new study, the scientists used their analysis of Twitter writings to show that there is a mathematical upper limit on how much predictive information a social network can hold--but that it makes little difference if the person is being profiled, or whose behaviour is being predicted, is on or off that network when their friends are on the network.

"You alone don't control your privacy on social media platforms," says UVM professor Jim Bagrow, "Your friends have a say too.