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Unpicking the privacy paradox: can structuration theory help to explain location-based privacy decisions?

Published:02 May 2013Publication History

ABSTRACT

Social Media and Web 2.0 tools have dramatically increased the amount of previously private data that users share on the Web; now with the advent of GPS-enabled smartphones users are also actively sharing their location data through a variety of applications and services. Existing research has explored people's privacy attitudes, and shown that the way people trade their personal data for services of value can be inconsistent with their stated privacy preferences (a phenomenon known as the privacy paradox). In this paper we present a study into privacy and location sharing, using quantitative analysis to show the presence of the paradox, and qualitative analysis in order to reveal the factors that lie behind it. Our analysis indicates that privacy decision-making can be seen as a process of structuration, in that people do not make location-sharing decisions as entirely free agents and are instead heavily influenced by contextual factors (external structures) during trade-off decisions. Collectively these decisions may themselves become new structures influencing future decisions. Our work has important consequences both for the understanding of how users arrive at privacy decisions, and also for the potential design of privacy systems.

References

  1. Acquisti, A. Nudging privacy: The behavioral economics of personal information. Security & Privacy, IEEE 7.6 (2009), 82--85. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Acquisti, A., Grossklags, J. What can behavioral economics teach us about privacy. DIGITAL PRIVACY (2009), 329.Google ScholarGoogle Scholar
  3. Bettman, J. R., and M. F. Luce. Constructive Consumer Choice Processes. Journal of consumer research 25, no. 3 (1998), 187--217.Google ScholarGoogle Scholar
  4. Boyd, D., Eszter H. Facebook privacy settings: Who cares. First Monday 15.8 (2010): 2.Google ScholarGoogle ScholarCross RefCross Ref
  5. Brackenbury, I., Wong, T. Online Profile & Reputation Perceptions Study. Microsoft Corporation (2012).Google ScholarGoogle Scholar
  6. Brandimarte, L., Acquisti, A., Loewenstein, G. Misplaced confidences: Privacy and the control paradox. Social Psychological and Personality Science (2012).Google ScholarGoogle Scholar
  7. Braunstein, A., Granka, L., Staddon, J. Indirect content privacy surveys: measuring privacy without asking about it. In Proceedings of the Seventh Symposium on Usable Privacy and Security (p. 15). ACM Press, (2011), 15. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Desanctis, G. & Poole, M. S. Capturing the Complexity in Advanced Technology Use: Adaptive Structuration Theory. Organization Science. 5 (1994), 121--147.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Giddens, A. The constitution of society: Outline of the theory of structuration. Univ of California Press (1984).Google ScholarGoogle Scholar
  10. Hann, I. H., K. L. Hui, T. S. Lee, and I. P. L. Png. Online information privacy: Measuring the cost-benefit trade-off. 23rd International Conference on Information Systems, (2002).Google ScholarGoogle Scholar
  11. Hui, K., H. H. Teo, and S. Y. T. Lee. The Value of Privacy Assurance: An Exploratory Field Experiment. Mis Quarterl 31, no. 1 (2007), 19--33. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Jensen, C., Potts, C., Jensen, C.. Privacy practices of Internet users: self-reports versus observed behavior. International Journal of Human-Computer Studies, 63(1), (2005), 203--227. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Jones, M. R., Karsten, H.. Giddens's structuration theory and information systems research. Mis Quarterly, 32(1), (2008), 127--157. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Madden, M. Privacy management on social media sites. Pew Internet Report (2012).Google ScholarGoogle Scholar
  15. Mancini, C., Thomas, K., Rogers, Y., Price, B. A., Jedrzejczyk, L., Bandara, A. K., Nuseibeh, B. From spaces to places: emerging contexts in mobile privacy. In Proc. Ubicomp. ACM Press (2009), 1--10. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Norberg, P. A., D. R. Horne, and D. A. Horne. The Privacy Paradox: Personal Information Disclosure Intentions versus Behaviors. Journal of Consumer Affairs (2007), 100--126.Google ScholarGoogle ScholarCross RefCross Ref
  17. Odlyzko, A. Privacy, economics, and price discrimination on the Internet. In Proc. Electronic commerce, ACM Press (2003), 355--366. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Orlikowski, W., J. The duality of technology: Rethinking the concept of technology in organizations. Organization science 3, no. 3 (1992), 398--427.Google ScholarGoogle Scholar
  19. Seale, C. (Ed.). Researching society and culture. Sage Publications Limited, (2004).Google ScholarGoogle Scholar
  20. Spiekermann, S., Grossklags, J., Berendt, B. E-privacy in 2nd generation E-commerce: privacy preferences versus actual behavior. In Proc. Electronic Commerce. ACM Press (2001), 38--47. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Tang, K., Hong, J., Siewiorek, D. The implications of offering more disclosure choices for social location sharing. In Proc. Human factors in computing systems ACM Press (2012), 391--394. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Tsai, J. Y., Kelley, P., Drielsma, P., Cranor, L. F., Hong, J., & Sadeh, N. Who's viewed you?: the impact of feedback in a mobile location-sharing application. In Proc. Human factors in computing systems 2009, ACM Press (2009), 2003--2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Wiese, J., Kelley, P. G., Cranor, L. F., Dabbish, L., Hong, J. I., Zimmerman, J. Are you close with me? are you nearby?: investigating social groups, closeness, and willingness to share. In Proc. of the 13th International Conference on Ubiquitous Computing, (2011). Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Wills, C., E., Mihajlo Zeljkovic. A personalized approach to web privacy: awareness, attitudes and actions. Information Management & Computer Security 19.1 (2011): 53--73.Google ScholarGoogle ScholarCross RefCross Ref
  25. Zafeiropoulou, A. M., K. O'Hara, D. Millard, and C. Webber. Location Data and Privacy: A Framework for Analysis. In Bernard Stiegler (ed.), Réseaux sociaux: Culture politique et ingénierie des réseaux sociaux. FYP EDITIONS (2012), 185--200.Google ScholarGoogle Scholar
  26. Cavoukian, A. Operationalizing Privacy by Design: A Guide to Implementing Strong Privacy Practices. Information and Privacy Commissioner, Ontario, Canada, (2012).Google ScholarGoogle Scholar
  27. Nissenbaum, H. Privacy in Context. Technology, Policy, and the Integrity of Social Life. In Stanford Law Books, (2010). Google ScholarGoogle ScholarDigital LibraryDigital Library

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          cover image ACM Conferences
          WebSci '13: Proceedings of the 5th Annual ACM Web Science Conference
          May 2013
          481 pages
          ISBN:9781450318891
          DOI:10.1145/2464464

          Copyright © 2013 ACM

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          Publication History

          • Published: 2 May 2013

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