IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0214369.html
   My bibliography  Save this article

Predicting individual-level income from Facebook profiles

Author

Listed:
  • Sandra C Matz
  • Jochen I Menges
  • David J Stillwell
  • H Andrew Schwartz

Abstract

Information about a person’s income can be useful in several business-related contexts, such as personalized advertising or salary negotiations. However, many people consider this information private and are reluctant to share it. In this paper, we show that income is predictable from the digital footprints people leave on Facebook. Applying an established machine learning method to an income-representative sample of 2,623 U.S. Americans, we found that (i) Facebook Likes and Status Updates alone predicted a person’s income with an accuracy of up to r = 0.43, and (ii) Facebook Likes and Status Updates added incremental predictive power above and beyond a range of socio-demographic variables (ΔR2 = 6–16%, with a correlation of up to r = 0.49). Our findings highlight both opportunities for businesses and legitimate privacy concerns that such prediction models pose to individuals and society when applied without individual consent.

Suggested Citation

  • Sandra C Matz & Jochen I Menges & David J Stillwell & H Andrew Schwartz, 2019. "Predicting individual-level income from Facebook profiles," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-13, March.
    • Handle: RePEc:plo:pone00:0214369
    DOI: 10.1371/journal.pone.0214369
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0214369
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0214369&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0214369?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Berthon, Pierre R. & Pitt, Leyland F. & Plangger, Kirk & Shapiro, Daniel, 2012. "Marketing meets Web 2.0, social media, and creative consumers: Implications for international marketing strategy," Business Horizons, Elsevier, vol. 55(3), pages 261-271.
    2. Blau Francine D & Kahn Lawrence M, 2007. "The Gender Pay Gap," The Economists' Voice, De Gruyter, vol. 4(4), pages 1-6, June.
    3. Daniel Preoţiuc-Pietro & Svitlana Volkova & Vasileios Lampos & Yoram Bachrach & Nikolaos Aletras, 2015. "Studying User Income through Language, Behaviour and Affect in Social Media," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-17, September.
    4. H Andrew Schwartz & Johannes C Eichstaedt & Margaret L Kern & Lukasz Dziurzynski & Stephanie M Ramones & Megha Agrawal & Achal Shah & Michal Kosinski & David Stillwell & Martin E P Seligman & Lyle H U, 2013. "Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach," PLOS ONE, Public Library of Science, vol. 8(9), pages 1-16, September.
    5. William A. Darity & Patrick L. Mason, 1998. "Evidence on Discrimination in Employment: Codes of Color, Codes of Gender," Journal of Economic Perspectives, American Economic Association, vol. 12(2), pages 63-90, Spring.
    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. Erik Hermann, 2022. "Leveraging Artificial Intelligence in Marketing for Social Good—An Ethical Perspective," Journal of Business Ethics, Springer, vol. 179(1), pages 43-61, August.
    2. Min Liu & Sajid Anwar, 2024. "Analyzing horizontal integration and market efficiency in platform enterprises: A case study of exchanges," Economics and Politics, Wiley Blackwell, vol. 36(2), pages 1076-1089, July.

    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. Jacob Levy Abitbol & Eric Fleury & Márton Karsai, 2019. "Optimal Proxy Selection for Socioeconomic Status Inference on Twitter," Complexity, Hindawi, vol. 2019, pages 1-15, May.
    2. Baumann, Chris & Timming, Andrew R. & Gollan, Paul J., 2016. "Taboo tattoos? A study of the gendered effects of body art on consumers' attitudes toward visibly tattooed front line staff," Journal of Retailing and Consumer Services, Elsevier, vol. 29(C), pages 31-39.
    3. Marlene Kim, 2013. "Race and ethnicity in the workplace," Chapters, in: Deborah M. Figart & Tonia L. Warnecke (ed.), Handbook of Research on Gender and Economic Life, chapter 14, pages 218-235, Edward Elgar Publishing.
    4. Iga Magda & Ewa Cukrowska-Torzewska, 2019. "Gender wage gap in the workplace: Does the age of the firm matter?," IBS Working Papers 01/2019, Instytut Badan Strukturalnych.
    5. Jean M. Twenge & Hannah VanLandingham & W. Keith Campbell, 2017. "The Seven Words You Can Never Say on Television: Increases in the Use of Swear Words in American Books, 1950-2008," SAGE Open, , vol. 7(3), pages 21582440177, August.
    6. Brahim Boudarbat & Marie Connolly, 2013. "The gender wage gap among recent post‐secondary graduates in Canada: a distributional approach," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 46(3), pages 1037-1065, August.
    7. Chen, Natalie & Conconi, Paola & Perroni, Carlo, 2007. "Women’s Earning Power and the “Double Burden” of Market and Household Work," The Warwick Economics Research Paper Series (TWERPS) 800, University of Warwick, Department of Economics.
    8. Omar Arias & Gustavo Yamada & Luis Tejerina, 2004. "Education, family background and racial earnings inequality in Brazil," International Journal of Manpower, Emerald Group Publishing Limited, vol. 25(3/4), pages 355-374, April.
    9. Filip Gesiarz & Jan-Emmanuel De Neve & Tali Sharot, 2020. "The motivational cost of inequality: Opportunity gaps reduce the willingness to work," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-18, September.
    10. He, Simin, 2019. "Minority advantage and disadvantage in competition and coordination," Journal of Economic Behavior & Organization, Elsevier, vol. 163(C), pages 464-482.
    11. Rydén, Pernille & Ringberg, Torsten & Wilke, Ricky, 2015. "How Managers' Shared Mental Models of Business–Customer Interactions Create Different Sensemaking of Social Media," Journal of Interactive Marketing, Elsevier, vol. 31(C), pages 1-16.
    12. Javier Cano-Urbina & Patrick L. Mason, 2016. "Acculturation and the labor market in Mexico," IZA Journal of Labor Policy, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-29, December.
    13. Emmanuel K. Yiridoe, 2021. "Fostering a culture of equity, diversity, and inclusion in the Canadian agricultural economics profession," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 69(1), pages 5-15, March.
    14. Hinnerich, Björn Tyrefors & Höglin, Erik & Johannesson, Magnus, 2011. "Ethnic Discrimination in High School Grading: Evidence from a Field Experiment," SSE/EFI Working Paper Series in Economics and Finance 733, Stockholm School of Economics, revised 27 Jun 2011.
    15. Marrero,Gustavo Alberto & Rodríguez,Juan Gabriel & Van Der Weide,Roy, 2021. "Does Race and Gender Inequality Impact Income Growth ?," Policy Research Working Paper Series 9865, The World Bank.
    16. Francois, Patrick & van Ours, Jan C., 2000. "Gender Wage Differentials in a Competitive Labor Market: The Household Interaction Effect," IZA Discussion Papers 202, Institute of Labor Economics (IZA).
    17. Chen, Yiu Por (Vincent) & Zhang, Yuan, 2018. "A decomposition method on employment and wage discrimination and its application in urban China (2002–2013)," World Development, Elsevier, vol. 110(C), pages 1-12.
    18. Gabriel Montes-Rojas & Lucas Siga & Ram Mainali, 2017. "Mean and quantile regression Oaxaca-Blinder decompositions with an application to caste discrimination," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 15(3), pages 245-255, September.
    19. Witek-Hajduk Marzanna K. & Zaborek Piotr, 2022. "Social media use in international marketing: Impact on brand and firm performance," International Journal of Management and Economics, Warsaw School of Economics, Collegium of World Economy, vol. 58(2), pages 121-142, June.
    20. repec:wyi:journl:002164 is not listed on IDEAS
    21. Wang, Tien & Lee, Fu-Yu, 2020. "Examining customer engagement and brand intimacy in social media context," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).

    More about this item

    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:plo:pone00:0214369. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.