Privacy wizards for social networking sites

12 years 8 months ago
Privacy wizards for social networking sites
Privacy is an enormous problem in online social networking sites. While sites such as Facebook allow users fine-grained control over who can see their profiles, it is difficult for average users to specify this kind of detailed policy. In this paper, we propose a template for the design of a social networking privacy wizard. The intuition for the design comes from the observation that real users conceive their privacy preferences (which friends should be able to see which information) based on an implicit set of rules. Thus, with a limited amount of user input, it is usually possible to build a machine learning model that concisely describes a particular user’s preferences, and then use this model to configure the user’s privacy settings automatically. As an instance of this general framework, we have built a wizard based on an active learning paradigm called uncertainty sampling. The wizard iteratively asks the user to assign privacy “labels” to selected (“informative”...
Lujun Fang, Kristen LeFevre
Added 14 May 2010
Updated 14 May 2010
Type Conference
Year 2010
Where WWW
Authors Lujun Fang, Kristen LeFevre
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