Analyzing facebook privacy settings: user expectations vs. reality

  • Authors:

  • Yabing Liu;Krishna P. Gummadi;Balachander Krishnamurthy;Alan Mislove

  • Affiliations:

  • Northeastern University, Boston, MA, USA;MPI-SWS, Saarbrücken/Kaiserslautern, Germany;AT&T Labs-Research, New Jersey, USA;Northeastern University, Boston, MA, USA

  • Venue:
  • Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
  • Year:
  • 2011

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Abstract

The sharing of personal data has emerged as a popular activity over online social networking sites like Facebook. As a result, the issue of online social network privacy has received significant attention in both the research literature and the mainstream media. Our overarching goal is to improve defaults and provide better tools for managing privacy, but we are limited by the fact that the full extent of the privacy problem remains unknown; there is little quantification of the incidence of incorrect privacy settings or the difficulty users face when managing their privacy. In this paper, we focus on measuring the disparity between the desired and actual privacy settings, quantifying the magnitude of the problem of managing privacy. We deploy a survey, implemented as a Facebook application, to 200 Facebook users recruited via Amazon Mechanical Turk. We find that 36% of content remains shared with the default privacy settings. We also find that, overall, privacy settings match users' expectations only 37% of the time, and when incorrect, almost always expose content to more users than expected. Finally, we explore how our results have potential to assist users in selecting appropriate privacy settings by examining the user-created friend lists. We find that these have significant correlation with the social network, suggesting that information from the social network may be helpful in implementing new tools for managing privacy.