Do you act one way around people and have an alter ego online?
You’re definitely not alone.
How about when you shop online? You may be surprised.
According to a new University of Vermont study, privacy on social media is like secondhand smoke: It’s controlled by the people around you.
But it definitely affects you, and probably not in a good way.
“Individual choice has long been considered a bedrock principle of online privacy. If you don’t want to be on Facebook, you can leave or not sign up in the first place. Then your behavior will be your own private business, right?” a release about the study posits.
The new study presents powerful evidence that the answer to that question is no. The study was published Jan. 21 in the journal Nature Human Behavior.
A team of scientists, from the University of Vermont and the University of Adelaide, gathered more than 30 million public posts on Twitter from 13,905 users. With this data, they showed that information within the Twitter messages from eight or nine of a person’s contacts make it possible to predict that person’s later tweets as accurately as if they were looking directly at that person’s own Twitter feed.
The study also shows that if a person leaves a social media platform — or never joined — the online posts and words of their friends still provide about 95 percent of the “potential predictive accuracy,” the scientists write, of a person’s future activities — even without any of that person’s data.
Conversely, when you sign up for Facebook or another social media platform, “you think you’re giving up your information, but you’re giving up your friends’ information too!” wrote University of Vermont mathematician James Bagrow, who led the new research.
What it demonstrates is that privacy matters.
“You alone don’t control your privacy on social media platforms,” says UVM professor Jim Bagrow. “Your friends have a say, too.”
The 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 new study shows that, at least in theory, a company, government or other actor can accurately profile a person (think political party, favorite products, religious commitments) from their friends, even if they’ve never been on social media or delete their account.
“There’s no place to hide in a social network,” says Lewis Mitchell, a co-author on the new study, who was a post-doctoral researcher at the University of Vermont and is now senior lecturer in applied mathematics at the University of Adelaide in Australia.
How information moves on social media platforms, like Facebook and Twitter, has become a powerful factor in protest movements, national elections and the rise and fall of commercial brands. (It also is everywhere … and “it” knows what you are buying or want to buy.)
“In order to sell extremely targeted advertisements, they need to know as much as they can about us, and have created social networks that let us connect with friends and strangers alike, or they provided useful tools like web search and email in order to collect this information,” Mitchell explained to the online tech magazine Sputnik. “Amazon is related but slightly different in that it gathers significant information about us by what we search for and ultimately purchase on their website in order to show us a combination of recommended items we may be interested in as well as targeted product-placement advertisements.”
And it translates to big money.
“The services these companies provide are effectively a data-collection front for their advertising businesses, which couldn’t exist without having us as users of their services. They have taken advantage of the basic fact of humans being social creatures in order to profit greatly: Twitter had $2.44 billion in revenue in 2017, Facebook’s was $40.65 billion and Google’s parent company Alphabet had revenue of $110.86 billion.”
Along the way, people on these platforms reveal massive amounts of information about themselves — and their friends. Go figure.
According to the release, scientists have not known if there is a fundamental limit to how much predictability is contained within this tidal wave of 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 being profiled, or whose behavior is being predicted, is on or off that network when their friends are on the network.