Social-networking sites (e.g., Facebook, MySpace, LinkedIn, etc.) and other online collaborative tools have emerged as places where people can post and share information. This information-sharing has many benefits, ranging from practical (e.g., sharing a business document) to purely social (e.g., communicating with distant friends). At the same time, information sharing inevitably poses significant threats to user privacy. In social-networking sites, for example, documented threats range from identity theft to digital stalking and personalized spam. As a result, a growing number of such sites allow individual users to specify fine-grained policies that indicate who can access their data, and to what extent. However, studies have consistently shown that most end-users find the task of specifying access-control policies for their own data overwhelming; as a result, users often skip the process altogether. The goal of this project is to help collaborative and social-media users gain control of their data. To that end, the project will include three main components: assisted specification, feedback, and refinement recommendations. To assist users in initially specifying access-control policies for their data, the project will develop a "privacy wizard," which employs data mining and machine learning methods, including active learning, to construct an accurate policy, with minimal input from the user. To provide feedback regarding existing privacy settings, the project will pursue two approaches: aggregate scores and visualizations. For example, an aggregate score can be used to concisely explain to the user how her settings differ from those of other users. Preliminary work found that Item Response Theory (IRT) can be used effectively for this purpose. Finally, the project will consider how aggregate scores and visual feedback can be enriched with recommendations for refinements to help the user achieve an expressed level of social exposure. Online collaborative tools and social media offer great promise in a number of arenas. In addition to communicating with friends via social networking sites, collaborative tools are now used in fields as diverse as business, medicine and education. However, the absence of usable privacy and access control prevents such tools from realizing their full potential. Results of this project will be disseminated via prototype implementations, as well as research publications. New undergraduate and graduate curriculum modules will also increase awareness of the importance of policy-specification and emerging research in this area.
TC: Small: Collaborative Research: User-centric Privacy Control for Collaborative Social Media