E-privacy in 2nd generation E-commerce: privacy preferences versus actual behavior
Proceedings of the 3rd ACM conference on Electronic Commerce
The quality of online social relationships
Communications of the ACM - How the virtual inspires the real
Location disclosure to social relations: why, when, & what people want to share
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A study of preferences for sharing and privacy
CHI '05 Extended Abstracts 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
NSDI'06 Proceedings of the 3rd conference on Networked Systems Design & Implementation - Volume 3
Privacy in Location-Aware Computing Environments
IEEE Pervasive Computing
SybilLimit: A Near-Optimal Social Network Defense against Sybil Attacks
SP '08 Proceedings of the 2008 IEEE Symposium on Security and Privacy
Predicting tie strength with social media
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
User interactions in social networks and their implications
Proceedings of the 4th ACM European conference on Computer systems
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
DHT routing using social links
IPTPS'04 Proceedings of the Third international conference on Peer-to-Peer Systems
Imagined communities: awareness, information sharing, and privacy on the facebook
PET'06 Proceedings of the 6th international conference on Privacy Enhancing Technologies
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We examine the correlation between user interactions and self reported information revelation preferences for users of the popular Online Social Network (OSN), Facebook. Our primary goal is to explore the use of indicators of tie strength to inform localized, per-user privacy preferences for users and their ties within OSNs. We examine the limitations of such an approach and discuss future plans to incorporate this approach into the development of an automated system for helping users define privacy policy. As part of future work, we discuss how to define/expand policy to the entire social network. We also present additional collected data similar to other studies such as perceived tie strength and information revelation preferences for OSN users.