IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_9571.html

Facebook Shadow Profiles

Author

Listed:
  • Luis Aguiar
  • Christian Peukert
  • Maximilian Schaefer
  • Hannes Ullrich

Abstract

Data is often at the core of digital products and services, especially when related to online advertising. This has made data protection and privacy a major policy concern. When surfing the web, consumers leave digital traces that can be used to build user profiles and infer preferences. We quantify the extent to which Facebook can track web behavior outside of their own platform. The network of engagement buttons, placed on third-party websites, lets Facebook follow users as they browse the web. Tracking users outside its core platform enables Facebook to build shadow profiles. For a representative sample of US internet users, 52 percent of websites visited, accounting for 40 percent of browsing time, employ Facebook’s tracking technology. Small differences between Facebook users and non-users are largely explained by differing user activity. The extent of shadow profiling Facebook may engage in is similar on privacy-sensitive domains and across user demographics, documenting the possibility for indiscriminate tracking.

Suggested Citation

  • Luis Aguiar & Christian Peukert & Maximilian Schaefer & Hannes Ullrich, 2022. "Facebook Shadow Profiles," CESifo Working Paper Series 9571, CESifo.
    • Handle: RePEc:ces:ceswps:_9571
    as

    Download full text from publisher

    File URL: https://www.ifo.de/DocDL/cesifo1_wp9571.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Garrett A. Johnson & Scott K. Shriver & Shaoyin Du, 2020. "Consumer Privacy Choice in Online Advertising: Who Opts Out and at What Cost to Industry?," Marketing Science, INFORMS, vol. 39(1), pages 33-51, January.
    2. Catarina Sismeiro & Ammara Mahmood, 2018. "Competitive vs. Complementary Effects in Online Social Networks and News Consumption: A Natural Experiment," Management Science, INFORMS, vol. 64(11), pages 5014-5037, November.
    3. Anna, Petrenko, . "Мaркування готової продукції як складова частина інформаційного забезпечення маркетингової діяльності підприємств овочепродуктового підкомплексу," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 2(01).
    4. Michael Trusov & Liye Ma & Zainab Jamal, 2016. "Crumbs of the Cookie: User Profiling in Customer-Base Analysis and Behavioral Targeting," Marketing Science, INFORMS, vol. 35(3), pages 405-426, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maximilian Schaefer, 2025. "When Should we Expect Non-Decreasing Returns from Data in Prediction Tasks?," Papers 2503.03602, arXiv.org.
    2. Martin Kögler & Katharina Paulick & Jürgen Scheffran & Mario Birkholz, 2024. "Sustainable use of a smartphone and regulatory needs," Sustainable Development, John Wiley & Sons, Ltd., vol. 32(6), pages 6182-6200, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nico Neumann & Catherine E. Tucker & Levi Kaplan & Alan Mislove & Piotr Sapiezynski, 2024. "Data Deserts and Black Boxes: The Impact of Socio-Economic Status on Consumer Profiling," Management Science, INFORMS, vol. 70(11), pages 8003-8029, November.
    2. Hana Choi & Carl F. Mela & Santiago R. Balseiro & Adam Leary, 2020. "Online Display Advertising Markets: A Literature Review and Future Directions," Information Systems Research, INFORMS, vol. 31(2), pages 556-575, June.
    3. Tesary Lin & Avner Strulov-Shlain, 2025. "Choice Architecture, Privacy Valuations, and Selection Bias in Consumer Data," Marketing Science, INFORMS, vol. 44(6), pages 1321-1338, November.
    4. Tesary Lin & Avner Strulov-Shlain, 2023. "Choice Architecture, Privacy Valuations, and Selection Bias in Consumer Data," Papers 2308.13496, arXiv.org.
    5. Rene Laub & Klaus M. Miller & Bernd Skiera, 2023. "The Economic Value of User Tracking for Publishers," Papers 2303.10906, arXiv.org, revised Apr 2024.
    6. Nico Neumann & Catherine E. Tucker & Kumar Subramanyam & John Marshall, 2023. "Is first- or third-party audience data more effective for reaching the ‘right’ customers? The case of IT decision-makers," Quantitative Marketing and Economics (QME), Springer, vol. 21(4), pages 519-571, December.
    7. Vivian Welch & Christine M. Mathew & Panteha Babelmorad & Yanfei Li & Elizabeth T. Ghogomu & Johan Borg & Monserrat Conde & Elizabeth Kristjansson & Anne Lyddiatt & Sue Marcus & Jason W. Nickerson & K, 2021. "Health, social care and technological interventions to improve functional ability of older adults living at home: An evidence and gap map," Campbell Systematic Reviews, John Wiley & Sons, vol. 17(3), September.
    8. Erkmen Giray Aslim, 2019. "The Relationship Between Health Insurance and Early Retirement: Evidence from the Affordable Care Act," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 45(1), pages 112-140, January.
    9. Nihan Akyelken, 2017. "Mobility-Related Economic Exclusion: Accessibility and Commuting Patterns in Industrial Zones in Turkey," Social Inclusion, Cogitatio Press, vol. 5(4), pages 175-182.
    10. Ekaterina Aleksandrova & Kristian Behrens & Maria Kuznetsova, 2020. "Manufacturing (co)agglomeration in a transition country: Evidence from Russia," Journal of Regional Science, Wiley Blackwell, vol. 60(1), pages 88-128, January.
    11. Grazzini, Jakob & Richiardi, Matteo G. & Tsionas, Mike, 2017. "Bayesian estimation of agent-based models," Journal of Economic Dynamics and Control, Elsevier, vol. 77(C), pages 26-47.
    12. Dilme, Francesc, 2025. "Repeated trade with imperfect information about previous transactions," Theoretical Economics, Econometric Society, vol. 20(1), January.
    13. Chen, Cheng & Senga, Tatsuro & Sun, Chang & Zhang, Hongyong, 2023. "Uncertainty, imperfect information, and expectation formation over the firm’s life cycle," Journal of Monetary Economics, Elsevier, vol. 140(C), pages 60-77.
    14. Julie Vinck & Idunn Brekke, 2019. "Gender and education inequalities in parental employment when having a young child with increased care needs: Belgium and Norway compared," Working Papers 1904, Herman Deleeck Centre for Social Policy, University of Antwerp.
    15. Alvarez, Camila H. & Evans, Clare Rosenfeld, 2021. "Intersectional environmental justice and population health inequalities: A novel approach," Social Science & Medicine, Elsevier, vol. 269(C).
    16. Michal Gluszak & Remigiusz Gawlik & Malgorzata Zieba, 2019. "Smart and Green Buildings Features in the Decision-Making Hierarchy of Office Space Tenants: An Analytic Hierarchy Process Study," Administrative Sciences, MDPI, vol. 9(3), pages 1-16, July.
    17. Shisong Jiang, 2021. "“When Paradigms Are Out of Place”: Embracing Eclecticism in Legal Scholarship by Academic Turns," Laws, MDPI, vol. 10(4), pages 1-16, October.
    18. Ilde Rizzo & Anna Mignosa (ed.), 2013. "Handbook on the Economics of Cultural Heritage," Books, Edward Elgar Publishing, number 14326.
    19. repec:spo:wpmain:info:hdl:2441/50jd34uldo9jioklc7b0dpu4ej is not listed on IDEAS
    20. Natalia Danzer & Martin Halla & Nicole Schneeweis & Martina Zweimüller, 2022. "Parental Leave, (In)formal Childcare, and Long-Term Child Outcomes," Journal of Human Resources, University of Wisconsin Press, vol. 57(6), pages 1826-1884.
    21. Jingjing Li & Haiyang Feng & Nan Feng & Nan Yuan, 2026. "Optimal Data Collection Levels for Two-Sided Software Platforms: Considering User Privacy Concerns," Information Systems Frontiers, Springer, vol. 28(1), pages 249-271, February.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • D18 - Microeconomics - - Household Behavior - - - Consumer Protection
    • L4 - Industrial Organization - - Antitrust Issues and Policies
    • L5 - Industrial Organization - - Regulation and Industrial Policy
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_9571. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/cesifde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.