The study, published in the journal Nature Human Behaviour on Tuesday, found that deleting an account was of no use as an individual could be profiled from data taken from friends' posts.
The researchers analysed the content of more than 30 million tweets, using information theory from mathematics and probability to test the predictability of individuals’ behaviour, based on what they published online.
Results showed that up to 95% of the potential accuracy was achievable for an individual using data from their friends alone. And data from eight to nine friends was enough to obtain predictability comparable to that using only the individual's data.
“Telling people to delete your account in order to protect your privacy is not enough, as profiling information such as someone’s political affiliations or leisure interests can be determined from your friends’ posts.
"It's like listening in on one end of a phone call. Even though you can't hear the person on the other end of the line, you can still find out a lot of information about them from the one-sided conversation you can hear."
“Many people know they are giving out access to their information when choosing to use an online platform, but they think it’s only information about themselves,” says co-author Dr James Bagrow, assistant professor, Mathematics and Statistics and Vermont Complex Systems Centre at the University of Vermont.
“But it’s not an individual choice: they’re also giving away information about their friends.”
Dr Mitchell added: “There are benefits from being able to predict behaviour. Social media platforms use this principle to target information so that you receive posts that you are interested in.
“But of course there is a dark side as well, such as the potential for the creation of ‘filter bubbles’. For instance in a political debate, people may be only exposed to one type of information and may not receive any opposing views.”