Privacy Preferences vs. Privacy Settings: An Exploratory Facebook Study

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 782)


Attacks on confidential data on the Internet is increasing. The reachability to users’ data needs stricter control. One way to do this by the user is applying proper privacy settings. Research finds there is slackness in online users’ applying proper privacy settings but no such work has focused on the reasons behind the slackness behavior. Our work aimed at studying user slackness behavior and investigating the human factors involved on such behavior. We evaluated the extent to which FB users’ privacy settings match their privacy preferences, whether FB user privacy setting behavior is dependent on age, gender, or education demographics, and the effectiveness of FB’s privacy settings. Our results validated user slackness in privacy settings and suggested a significant association between the age categories and the privacy settings behavior. The results also suggested that FB’s privacy settings system is not effective for its diverse demographic user base.


Online social networks (OSNs) Online privacy Communication-human information processing (C-HIP) model Facebook 


  1. 1.
    Govani, T., Pashley, H.: Student awareness of the privacy implications when using Facebook. Unpublished Paper Presented at the “Privacy Poster Fair” at the Carnegie Mellon University School of Library and Information Science, vol. 9, pp. 1–17 (2005)Google Scholar
  2. 2.
    Jones, H., Soltren, J.H.: Facebook: threats to privacy. Project MAC: MIT Project on Mathematics and Computing, vol. 1, pp. 1–76. (2005)Google Scholar
  3. 3.
    Fong, P.W.L., Anwar, M., Zhao, Z.: A privacy preservation model for Facebook-style social network systems. In: Backes, M., Ning, P. (eds.) Computer Security – ESORICS 2009. Lecture Notes in Computer Science, vol. 5789. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  4. 4.
    Bonneau, J., Anderson, R., Stajano, F.: Eight friends are enough: social graph approximation via public listings. In: Proceedings of the Second ACM EuroSys Workshop on Social Network Systems, pp. 13–18. ACM, March 2009Google Scholar
  5. 5.
    Liu, Y., Gummadi, K.P., Krishnamurthy, B., Mislove, A.: Analyzing Facebook privacy settings: user expectations vs. reality. In: Proceedings of the 2011 ACM SIGCOMM Conference on Internet Measurement Conference, pp. 61–70. ACM, November 2011Google Scholar
  6. 6.
    Conzola, C., Wogalter, M.S.: A Communication-Human Information Processing (C-HIP) approach to warning effectiveness in the workplace. J. Risk Res. 4(4), 309–322 (2001). Scholar
  7. 7.
    Lasswell, H.D.: The structure and function of communication in society. In: Bryson, L. (ed.) The Communication of Ideas. Wiley, New York (1948)Google Scholar
  8. 8.
    Acquisti, A., Gross, R.: Imagined communities: awareness, information sharing and privacy on the Facebook. In: Danezis, G., Golle, P. (eds.) Privacy Enhancing Technologies, pp. 36–58. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  9. 9.
    Gross, R., Acquisti, A.: Information revelation and privacy in online social. In: Proceedings of the 2005 ACM Workshop on Privacy in the Electronic Society, pp. 71–80 (2005)Google Scholar
  10. 10.
    Lipford, H.R., Besmer, A., Watson, J.: Understanding privacy settings in Facebook with an audience view. UPSEC 8, 1–8 (2008)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.North Carolina A&T State UniversityGreensboroUSA

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