skip to main content
10.1145/2464464.2464503acmconferencesArticle/Chapter ViewAbstractPublication PageswebsciConference Proceedingsconference-collections
research-article

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

Published: 02 May 2013 Publication 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.
[2]
Acquisti, A., Grossklags, J. What can behavioral economics teach us about privacy. DIGITAL PRIVACY (2009), 329.
[3]
Bettman, J. R., and M. F. Luce. Constructive Consumer Choice Processes. Journal of consumer research 25, no. 3 (1998), 187--217.
[4]
Boyd, D., Eszter H. Facebook privacy settings: Who cares. First Monday 15.8 (2010): 2.
[5]
Brackenbury, I., Wong, T. Online Profile & Reputation Perceptions Study. Microsoft Corporation (2012).
[6]
Brandimarte, L., Acquisti, A., Loewenstein, G. Misplaced confidences: Privacy and the control paradox. Social Psychological and Personality Science (2012).
[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.
[8]
Desanctis, G. & Poole, M. S. Capturing the Complexity in Advanced Technology Use: Adaptive Structuration Theory. Organization Science. 5 (1994), 121--147.
[9]
Giddens, A. The constitution of society: Outline of the theory of structuration. Univ of California Press (1984).
[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).
[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.
[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.
[13]
Jones, M. R., Karsten, H. Giddens's structuration theory and information systems research. Mis Quarterly, 32(1), (2008), 127--157.
[14]
Madden, M. Privacy management on social media sites. Pew Internet Report (2012).
[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.
[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.
[17]
Odlyzko, A. Privacy, economics, and price discrimination on the Internet. In Proc. Electronic commerce, ACM Press (2003), 355--366.
[18]
Orlikowski, W., J. The duality of technology: Rethinking the concept of technology in organizations. Organization science 3, no. 3 (1992), 398--427.
[19]
Seale, C. (Ed.). Researching society and culture. Sage Publications Limited, (2004).
[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.
[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.
[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.
[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).
[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.
[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.
[26]
Cavoukian, A. Operationalizing Privacy by Design: A Guide to Implementing Strong Privacy Practices. Information and Privacy Commissioner, Ontario, Canada, (2012).
[27]
Nissenbaum, H. Privacy in Context. Technology, Policy, and the Integrity of Social Life. In Stanford Law Books, (2010).

Cited By

View all
  • (2024)Typology of Intelligent Information Technology Usage Groups and Determinants of Private Information Provision Intention : Focusing on Latent Class Analysis of Digital CompetenceKorean Journal of Journalism & Communication Studies10.20879/kjjcs.2024.68.1.00368:1(78-120)Online publication date: 29-Feb-2024
  • (2024)Understanding Users' Perspectives on Location Privacy Management on iPhonesProceedings of the ACM on Human-Computer Interaction10.1145/36765298:MHCI(1-25)Online publication date: 24-Sep-2024
  • (2024)Can Stress Put Digital Privacy at Risk? Evidence from a Controlled Experiment Examining the Impact of Acute Stress on Privacy Decisions on a Simulated Social Network SiteCyberpsychology, Behavior, and Social Networking10.1089/cyber.2023.0687Online publication date: 19-Jul-2024
  • Show More Cited By

Index Terms

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

        Recommendations

        Comments

        Information & Contributors

        Information

        Published In

        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
        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

        Sponsors

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        Published: 02 May 2013

        Permissions

        Request permissions for this article.

        Check for updates

        Author Tags

        1. location data
        2. privacy paradox
        3. privacy trade-off
        4. structuration

        Qualifiers

        • Research-article

        Funding Sources

        Conference

        WebSci '13
        Sponsor:
        WebSci '13: Web Science 2013
        May 2 - 4, 2013
        Paris, France

        Acceptance Rates

        Overall Acceptance Rate 245 of 933 submissions, 26%

        Upcoming Conference

        Websci '25
        17th ACM Web Science Conference
        May 20 - 24, 2025
        New Brunswick , NJ , USA

        Contributors

        Other Metrics

        Bibliometrics & Citations

        Bibliometrics

        Article Metrics

        • Downloads (Last 12 months)51
        • Downloads (Last 6 weeks)7
        Reflects downloads up to 07 Mar 2025

        Other Metrics

        Citations

        Cited By

        View all
        • (2024)Typology of Intelligent Information Technology Usage Groups and Determinants of Private Information Provision Intention : Focusing on Latent Class Analysis of Digital CompetenceKorean Journal of Journalism & Communication Studies10.20879/kjjcs.2024.68.1.00368:1(78-120)Online publication date: 29-Feb-2024
        • (2024)Understanding Users' Perspectives on Location Privacy Management on iPhonesProceedings of the ACM on Human-Computer Interaction10.1145/36765298:MHCI(1-25)Online publication date: 24-Sep-2024
        • (2024)Can Stress Put Digital Privacy at Risk? Evidence from a Controlled Experiment Examining the Impact of Acute Stress on Privacy Decisions on a Simulated Social Network SiteCyberpsychology, Behavior, and Social Networking10.1089/cyber.2023.0687Online publication date: 19-Jul-2024
        • (2024)GEOPRIVACY KNOWLEDGE, ATTITUDES, AND BEHAVIORS in CONTEMPORARY CHINAGeographical Review10.1080/00167428.2024.2422873(1-25)Online publication date: 14-Nov-2024
        • (2024)To Ban, or Not to Ban, this Is the D(AI)lemma: An Analysis of Ecosystem LandscapesDigital (Eco) Systems and Societal Challenges10.1007/978-3-031-75586-6_18(335-353)Online publication date: 14-Dec-2024
        • (2023)신체 정보를 활용한 사이즈 추천 서비스에 대한 소비자의 정보 프라이버시 염려와 정보 제공 의도Journal of the Korean Society of Clothing and Textiles10.5850/JKSCT.2023.47.3.44247:3(442-458)Online publication date: 30-Jun-2023
        • (2023)UNDERSTANDING PRIVACY PARADOX: AN EXPERIMENTAL APPROACH TO STUDY PRIVACY CONCERNS AND ACTUAL DISCLOSURE AMONG APP USERSJournal of Organizational Computing and Electronic Commerce10.1080/10919392.2023.225132833:3-4(97-116)Online publication date: 31-Aug-2023
        • (2023)“Hello, Fellow Villager!”: Perceptions and Impact of Displaying Users’ Locations on WeiboHuman-Computer Interaction – INTERACT 202310.1007/978-3-031-42286-7_29(511-532)Online publication date: 25-Aug-2023
        • (2022)SOSYAL AĞLARDA VERİ GİZLİLİĞİ: TÜRKİYE’DE WHATSAPP GİZLİLİK SÖZLEŞMESİNE GÖSTERİLEN TEPKİLERİNİN DUYGU ANALİZİDATA PRIVACY ON SOCIAL NETWORKS: SENTIMENT ANALYSIS ON REACTIONS IN TURKEY TO WHATSAPP’S CONFIDENTIALITY AGREEMENTKafkas Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi10.36543/kauiibfd.2022.03013:26(710-742)Online publication date: 27-Dec-2022
        • (2022)Harnessing Soft Logic to Represent the Privacy ParadoxInformatics10.3390/informatics90300549:3(54)Online publication date: 18-Jul-2022
        • Show More Cited By

        View Options

        Login options

        View options

        PDF

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader

        Figures

        Tables

        Media

        Share

        Share

        Share this Publication link

        Share on social media