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After analyzing 4,080 Facebook profiles from the MIT network, we determined that the percentage of a given user’s friends who self–identify as gay male is strongly correlated with the sexual orientation of that user, and we developed a logistic regression classifier with strong predictive power.
If the majority of your friends were male, one might predict you to be male.Public information about one’s coworkers, friends, family, and acquaintances, as well as one’s associations with them, implicitly reveals private information.Social networking Web sites, e–mail, instant messaging, telephone, and Vo IP are all technologies steeped in network data — data relating one person to another.Network data shifts the locus of information control away from individuals, as the individual’s traditional and absolute discretion is replaced by that of his social network.Our research demonstrates a method for accurately predicting the sexual orientation of Facebook users by analyzing friendship associations.If many of your friends were a particular race, one might predict you to be that race.
If many of your friends were gay, one might predict you to be gay.
This predictive power works even though one knows nothing about you, as long as one knows something about your friends.
With the advent of computer–mediated communication, it has become disturbingly easy to log and track the web of human interactions.
The phone company stores data on who calls whom, for example, and that data builds a social graph.
Likewise, consider a social networking Web site such as Facebook where connections between users are clearly visible.
Facebook allows each user to create a profile, and users can also designate other Facebook users as “friends.” Although Facebook users can control the content of their own profiles, they cannot control the content of their friends’ profiles.