Researchers find a way to identify individuals in supposedly anonymous social-network data. One way for social networks to make money is by sharing information about users with advertisers and others who are interested in understanding consumer behavior and exploiting online trends.
Social networks typically promise to remove “personally identifying information” before sharing this data, to protect users’ privacy. But researchers has found that, combined with readily available data from other online sources, this anonymized data can still reveal sensitive information about users.
In tests involving the photo-sharing site Flickr and the microblogging service Twitter, the researchers were able to identify a third of the users with accounts on both sites simply by searching for recognizable patterns in anonymized network data. Both Twitter and Flickr display user information publicly, so the researchers anonymized much of the data in order to test their algorithms.
The researchers wanted to see if they could extract sensitive information about individuals using just the connections between users, even if almost all of the names, addresses, and other forms of personally identifying information had been removed. They found that they could, provided they could compare these patterns with those from another social-network graph where some user information was accessible.
Data from social networks–particularly the pattern of friendship between users–can be valuable to advertisers. Most social networks plan to make money by sharing this information, while advertisers hope to employ it to find a particularly influential user and target her with advertising to reach her network of friends, for example.
The researchers say that it is fairly easy to find non anonymous social-network data: the connections between friends in many networks, such as Twitter, are made public by default.