For instance, computer researchers were able to determine a person's location within a 100 metre radius with 85 percent accuracy by using only the location of that person's friends.
They were also able to predict a person's Twitter friendships with high accuracy, even when that person's profile was kept private.
In one experiment, Adam Sadilek, Henry Kautz, and Jeffrey Bigham from University of Rochester studied the messages and data of heavy Twitter users from New York City and Los Angeles to develop a computer model for determining human mobility and location.
The users, who sent out 100 or more tweets per month, had public profiles and enabled GPS location sharing. The location data of selected individuals was sampled over a two-week period, and then was ignored as the researchers tried to pinpoint their locations using only the information from their Twitter friends, according to a Rochester statement.
In more than eight out of 10 instances, they successfully figured out where the individuals lived to within one city block. "Once you learn about relationships from peoples' tweets, it makes sense that you can track them," said Sadilek, the project's first author. "My fiancee may be a good predictor of my location because we have breakfast together every morning."
The personal nature of the messages made it a little easier for the researchers to determine relationships. Sadilek explains that heavy Twitter users spend a great deal of time talking about themselves.
"It's harder than most people think it is to protect our privacy online," said Kautz, chairman of the Department of Computer Science at Rochester, "but there are ways to use this new reality for good."