BACKGROUND:  Recent years have seen a huge growth in online social networking sites such as Facebook, Myspace, and Friendster. Given the huge amount of personal data and social relationships available in online social networks, protecting one's personal privacy is a growing problem. Since private information can be inferred via social relationships, it is possible to infer private information even when such information is not shared.

INNOVATION:  The invention uses a method to infer with a high degree of accuracy personal information based on social networks.

POTENTIAL APPLICATIONS 

• For the end user: implementation in a personal privacy management and advising software tool
• For an online social networking provider: provide privacy evaluation as part of its service to end users
• For a product recommender: based on a user's interest on the set of attributes for a given product, using the social relationships among friends to infer which of his friends will also be interested in this product.

ADVANTAGES:  Currently, no social network services implement any privacy evaluation, alert, and recommendation techniques that could help end users easily evaluate and manage the level to which their private information is revealed. Neither does any personal software tool exist on the market that provides such functionality.

DEVELOPMENT-TO-DATE:  The concept has been developed and results of the experiment have been published.

Reference: UCLA Case No. 2007-626