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- Datasource
- Association for Computing Machinery
- Copyright
- Copyright © 2005 by ACM Inc.
- ISBN
- 1-59593-228-3
- doi
- 10.1145/1102199.1102214
- Publisher site
- See Article on Publisher Site
Abstract
Information Revelation and Privacy in Online Social Networks Ralph Gross Data Privacy Laboratory School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 Alessandro Acquisti H. John Heinz III School of Public Policy and Management Carnegie Mellon University Pittsburgh, PA 15213 [email protected] ABSTRACT Participation in social networking sites has dramatically increased in recent years. Services such as Friendster, Tribe, or the Facebook allow millions of individuals to create online pro Âles and share personal information with vast networks of friends - and, often, unknown numbers of strangers. In this paper we study patterns of information revelation in online social networks and their privacy implications. We analyze the online behavior of more than 4,000 Carnegie Mellon University students who have joined a popular social networking site catered to colleges. We evaluate the amount of information they disclose and study their usage of the site ™s privacy settings. We highlight potential attacks on various aspects of their privacy, and we show that only a minimal percentage of users changes the highly permeable privacy preferences. [email protected] commercial interest only arose well after the advent of the Internet.1 The rapid increase in participation in very recent years has been accompanied by a