IDEAS home Printed from https://ideas.repec.org/p/nbr/nberwo/23089.html
   My bibliography  Save this paper

Social Media and Fake News in the 2016 Election

Author

Listed:
  • Hunt Allcott
  • Matthew Gentzkow

Abstract

Following the 2016 U.S. presidential election, many have expressed concern about the effects of false stories (“fake news”), circulated largely through social media. We discuss the economics of fake news and present new data on its consumption prior to the election. Drawing on web browsing data, archives of fact-checking websites, and results from a new online survey, we find: (i) social media was an important but not dominant source of election news, with 14 percent of Americans calling social media their “most important” source; (ii) of the known false news stories that appeared in the three months before the election, those favoring Trump were shared a total of 30 million times on Facebook, while those favoring Clinton were shared 8 million times; (iii) the average American adult saw on the order of one or perhaps several fake news stories in the months around the election, with just over half of those who recalled seeing them believing them; and (iv) people are much more likely to believe stories that favor their preferred candidate, especially if they have ideologically segregated social media networks.

Suggested Citation

  • Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," NBER Working Papers 23089, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:23089
    Note: POL
    as

    Download full text from publisher

    File URL: http://www.nber.org/papers/w23089.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ariel Malka & Jon A. Krosnick & Gary Langer, 2009. "The Association of Knowledge with Concern About Global Warming: Trusted Information Sources Shape Public Thinking," Risk Analysis, John Wiley & Sons, vol. 29(5), pages 633-647, May.
    2. Hainmueller, Jens, 2012. "Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies," Political Analysis, Cambridge University Press, vol. 20(1), pages 25-46, January.
    3. Gerber, Alan S. & Gimpel, James G. & Green, Donald P. & Shaw, Daron R., 2011. "How Large and Long-lasting Are the Persuasive Effects of Televised Campaign Ads? Results from a Randomized Field Experiment," American Political Science Review, Cambridge University Press, vol. 105(1), pages 135-150, February.
    4. Guess, Andrew M., 2015. "Measure for Measure: An Experimental Test of Online Political Media Exposure," Political Analysis, Cambridge University Press, vol. 23(1), pages 59-75, January.
    5. Gregory J. Martin & Ali Yurukoglu, 2017. "Bias in Cable News: Persuasion and Polarization," American Economic Review, American Economic Association, vol. 107(9), pages 2565-2599, September.
    6. Gerber, Alan S. & Green, Donald P., 2000. "The Effects of Canvassing, Telephone Calls, and Direct Mail on Voter Turnout: A Field Experiment," American Political Science Review, Cambridge University Press, vol. 94(3), pages 653-663, September.
    7. Ruben Enikolopov & Maria Petrova & Ekaterina Zhuravskaya, 2011. "Media and Political Persuasion: Evidence from Russia," American Economic Review, American Economic Association, vol. 101(7), pages 3253-3285, December.
    8. Brett R. Gordon & Wesley R. Hartmann, 2013. "Advertising Effects in Presidential Elections," Marketing Science, INFORMS, vol. 32(1), pages 19-35, June.
    9. Prior, Markus & Sood, Gaurav & Khanna, Kabir, 2015. "You Cannot be Serious: The Impact of Accuracy Incentives on Partisan Bias in Reports of Economic Perceptions," Quarterly Journal of Political Science, now publishers, vol. 10(4), pages 489-518, December.
    10. Stefano DellaVigna & Matthew Gentzkow, 2010. "Persuasion: Empirical Evidence," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 643-669, September.
    11. Bullock, John G. & Gerber, Alan S. & Hill, Seth J. & Huber, Gregory A., 2015. "Partisan Bias in Factual Beliefs about Politics," Quarterly Journal of Political Science, now publishers, vol. 10(4), pages 519-578, December.
    12. Matthew Gentzkow & Jesse M. Shapiro, 2011. "Ideological Segregation Online and Offline," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 126(4), pages 1799-1839.
    13. Stefano DellaVigna & Ethan Kaplan, 2007. "The Fox News Effect: Media Bias and Voting," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 122(3), pages 1187-1234.
    14. Jörg L. Spenkuch & David Toniatti, 2016. "Political Advertising and Election Outcomes," CESifo Working Paper Series 5780, CESifo.
    15. Bartels, Larry M., 1993. "Messages Received: The Political Impact of Media Exposure," American Political Science Review, Cambridge University Press, vol. 87(2), pages 267-285, June.
    16. Alan Gerber & Donald Green, 2000. "The effects of canvassing, direct mail, and telephone contact on voter turnout: A field experiment," Natural Field Experiments 00248, The Field Experiments Website.
    Full references (including those not matched with items on IDEAS)

    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. Thomas Fujiwara & Karsten Müller & Carlo Schwarz, 2021. "The Effect of Social Media on Elections: Evidence from the United States," NBER Working Papers 28849, National Bureau of Economic Research, Inc.
    2. Thomas Fujiwara & Karsten Müller & Carlo Schwarz, 2021. "The Effect of Social Media on Elections: Evidence from the United States," NBER Working Papers 28849, National Bureau of Economic Research, Inc.
    3. Maria Petrova & Ananya Sen & Pinar Yildirim, 2020. "Social Media and Political Contributions: The Impact of New Technology on Political Competition," Papers 2011.02924, arXiv.org.
    4. Maria Petrova & Ananya Sen & Pinar Yildirim, 2021. "Social Media and Political Contributions: The Impact of New Technology on Political Competition," Management Science, INFORMS, vol. 67(5), pages 2997-3021, May.
    5. Sung Jae Jun & Sokbae Lee, 2023. "Identifying the Effect of Persuasion," Journal of Political Economy, University of Chicago Press, vol. 131(8), pages 2032-2058.
    6. repec:hal:journl:hal-03533356 is not listed on IDEAS
    7. Mitchell J. Lovett, 2019. "Empirical Research on Political Marketing: a Selected Review," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 6(3), pages 49-56, December.
    8. Juan Pablo Atal & José Ignacio Cuesta & Felipe González & Cristóbal Otero, 2024. "The Economics of the Public Option: Evidence from Local Pharmaceutical Markets," American Economic Review, American Economic Association, vol. 114(3), pages 615-644, March.
    9. repec:hal:spmain:info:hdl:2441/7jk88md0ar9hga662p2vjjq4kc is not listed on IDEAS
    10. Little, Andrew T., 2022. "Bayesian Explanations for Persuasion," OSF Preprints ygw8e, Center for Open Science.
    11. Cagé, Julia, 2020. "Media competition, information provision and political participation: Evidence from French local newspapers and elections, 1944–2014," Journal of Public Economics, Elsevier, vol. 185(C).
    12. Chun-Fang Chiang & Semin Kim & SunTak Kim & Chien-Hsun Lin & Ming-Jen Lin, 2019. "Can Partisan News Shift Political Preference and Voting Behavior? An Experimental Evidence from Taiwan's General Elections 2016," Working papers 2019rwp-147, Yonsei University, Yonsei Economics Research Institute.
    13. Matthew Gentzkow & Jesse M. Shapiro & Michael Sinkinson, 2011. "The Effect of Newspaper Entry and Exit on Electoral Politics," American Economic Review, American Economic Association, vol. 101(7), pages 2980-3018, December.
    14. Galasso, Vincenzo & Morelli, Massimo & Nannicini, Tommaso, 2022. "Fighting Populism on Its Own Turf: Experimental Evidence," CEPR Discussion Papers 17380, C.E.P.R. Discussion Papers.
    15. repec:hal:spmain:info:hdl:2441/478a1feno18otpdr60lclo4fuq is not listed on IDEAS
    16. Julia Cage, 2019. "Media competition, information provision and political participation:Evidence from French local newspapers and elections, 1944–2014," SciencePo Working papers hal-03567022, HAL.
    17. Cagé, Julia, 2017. "Media Competition, Information Provision and Political Participation: Evidence from French Local Newspapers and Elections, 1944," CEPR Discussion Papers 12198, C.E.P.R. Discussion Papers.
    18. Julia Cage, 2017. "Media Competition, Information Provision and Political Participation: Evidence from French Local Newspapers and Elections, 1944-2014," SciencePo Working papers Main hal-03393164, HAL.
    19. Iván M. Durán, 2018. "Television and electoral results in Catalonia," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 9(4), pages 423-456, November.
    20. Julia Cage, 2017. "Media Competition, Information Provision and Political Participation: Evidence from French Local Newspapers and Elections, 1944-2014," SciencePo Working papers hal-03393164, HAL.
    21. Andrew T Little, 2023. "Bayesian explanations for persuasion," Journal of Theoretical Politics, , vol. 35(3), pages 147-181, July.
    22. Tianyi Wang, 2021. "Media, Pulpit, and Populist Persuasion: Evidence from Father Coughlin," American Economic Review, American Economic Association, vol. 111(9), pages 3064-3092, September.
    23. Redlicki, B., 2017. "Spreading Lies," Cambridge Working Papers in Economics 1747, Faculty of Economics, University of Cambridge.

    More about this item

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D7 - Microeconomics - - Analysis of Collective Decision-Making
    • H0 - Public Economics - - General
    • J60 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - General

    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:nbr:nberwo:23089. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/nberrus.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.