Information revelation and privacy in online social networks
Proceedings of the 2005 ACM workshop on Privacy in the electronic society
Characterizing privacy in online social networks
Proceedings of the first workshop on Online social networks
On the leakage of personally identifiable information via online social networks
Proceedings of the 2nd ACM workshop on Online social networks
Friends only: examining a privacy-enhancing behavior in facebook
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Security and Privacy in Social Networks
IEEE Internet Computing
Exploiting vulnerability to secure user privacy on a social networking site
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Analyzing facebook privacy settings: user expectations vs. reality
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Imagined communities: awareness, information sharing, and privacy on the facebook
PET'06 Proceedings of the 6th international conference on Privacy Enhancing Technologies
Privacy attacks in social media using photo tagging networks: a case study with Facebook
Proceedings of the 1st Workshop on Privacy and Security in Online Social Media
Collaborative privacy management for third-party applications in online social networks
Proceedings of the 1st Workshop on Privacy and Security in Online Social Media
Caracterização qualitativa da sociabilidade no Facebook
Proceedings of the 12th Brazilian Symposium on Human Factors in Computing Systems
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Facebook, the largest social network nowadays currently has 901 million active users, with 526 million of them accessing the system daily. With a very rapid growth, Facebook has become a potential site for the collection of personal information by unauthorized individuals, leaving its users vulnerable to actions of violation of privacy, spamming and phishing. This article discusses the vulnerability of Facebook users based on their exposure in the network. To this end, we propose a numerical indicator capable of estimating the degree of vulnerability of each user. This indicator is a function of both the amount of personal content published by the user and the size of her network. We demonstrate the use of the proposed indicator in real data collected from 75,000 Facebook users.