Regulation is only way to stop social networks from learning more than we want, says researcher
Social networks have no incentive to inform users how data is gathered on them, a privacy researcher says
Online social networks are gathering information about their users that those people never intended to disclose, and government regulation may be the only way to stop the practice.
People deliberately disclose a great deal of their personal data to social networks such as Twitter, Facebook and LinkedIn, but the networks can use that information, and data about users' online behavior, to infer even more, allowing them to build extensive user profiles
Existing techniques already allow the social networks to determine the purchasing power, ethnicity or political affiliation of users who did not intend to disclose such information. Making such inferences without informing the users constitutes a severe threat to privacy, and allows unprecedented user profiling, he said.
"Knowing someone's political affiliation might not be so important here, but it might be very important in countries like Syria," Who added that kind of inferred data might have a big impact on someone's life there.
Indications of a user's purchasing power can also be useful for companies, he said. "Recently it was discovered that a hotel booking site showed more expensive hotels to Mac users that visited the site," Zimmermann said, referring to online booking site Orbitz, which showed site visitors rooms in more expensive hotels depending on the computer they used.
The problem is that social network users have no idea what information is pieced together about them, while from a privacy perspective, it should really be the user who is in control of the data, not the social network.
People can't know what data is inferred about them because they don't know what rules are used to build the extensive user profiles, he said. Moreover, the rule sets used by social networks evolve constantly. As users publicize new information and the provider gathers new data, new patterns emerge causing old patterns to change and it is impossible for a user to predict these changes, he said.
One way to prevent inferences being made from data is not to disclose it in the first place, but that is very hard for users to do when they don't know how an online service is combining information about them. Besides that, others might be disclosing the very information that they are trying to keep secret.