Unpacking "privacy" for a networked world
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Who gets to know what when: configuring privacy permissions in an awareness application
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Information revelation and privacy in online social networks
Proceedings of the 2005 ACM workshop on Privacy in the electronic society
Vizster: Visualizing Online Social Networks
INFOVIS '05 Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization
Balancing Systematic and Flexible Exploration of Social Networks
IEEE Transactions on Visualization and Computer Graphics
Expandable grids for visualizing and authoring computer security policies
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Understanding privacy settings in facebook with an audience view
UPSEC'08 Proceedings of the 1st Conference on Usability, Psychology, and Security
All My People Right Here, Right Now: management of group co-presence on a social networking site
Proceedings of the ACM 2009 international conference on Supporting group work
Inferring privacy policies for social networking services
Proceedings of the 2nd ACM workshop on Security and artificial intelligence
A Framework for Computing the Privacy Scores of Users in Online Social Networks
ICDM '09 Proceedings of the 2009 Ninth IEEE International Conference on Data Mining
Visual vs. compact: a comparison of privacy policy interfaces
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Privacy wizards for social networking sites
Proceedings of the 19th international conference on World wide web
The impact of social navigation on privacy policy configuration
Proceedings of the Sixth Symposium on Usable Privacy and Security
Feasibility of structural network clustering for group-based privacy control in social networks
Proceedings of the Sixth Symposium on Usable Privacy and Security
Oops, I did it again: mitigating repeated access control errors on facebook
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Imagined communities: awareness, information sharing, and privacy on the facebook
PET'06 Proceedings of the 6th international conference on Privacy Enhancing Technologies
Regroup: interactive machine learning for on-demand group creation in social networks
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Talking in circles: selective sharing in google+
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Retrospective privacy: managing longitudinal privacy in online social networks
Proceedings of the Ninth Symposium on Usable Privacy and Security
What you want is not what you get: predicting sharing policies for text-based content on facebook
Proceedings of the 2013 ACM workshop on Artificial intelligence and security
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Users' mental models of privacy and visibility in social networks often involve subgroups within their local networks of friends. Many social networking sites have begun building interfaces to support grouping, like Facebook's lists and "Smart Lists," and Google+'s "Circles." However, existing policy comprehension tools, such as Facebook's Audience View, are not aligned with this mental model. In this paper, we introduce PViz, an interface and system that corresponds more directly with how users model groups and privacy policies applied to their networks. PViz allows the user to understand the visibility of her profile according to automatically-constructed, natural sub-groupings of friends, and at different levels of granularity. Because the user must be able to identify and distinguish automatically-constructed groups, we also address the important sub-problem of producing effective group labels. We conducted an extensive user study comparing PViz to current policy comprehension tools (Facebook's Audience View and Custom Settings page). Our study revealed that PViz was comparable to Audience View for simple tasks, and provided a significant improvement for complex, group-based tasks, despite requiring users to adapt to a new tool. Utilizing feedback from the user study, we further iterated on our design, constructing PViz 2.0, and conducted a follow-up study to evaluate our refinements.