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Sharing News Left and Right: The Effects of Policies Targeting Misinformation on Social Media

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  • Daniel Ershov
  • Juan S. Morales

Abstract

We study Facebook’s and Twitter’s policy interventions which aimed to reduce the spread of misinformation during the 2020 US election. Facebook changed its news feed algorithm to reduce the visibility of content, while Twitter changed its user interface, nudging users to be thoughtful about sharing content. Using data on tweets and Facebook posts published by news media outlets, we show both policies significantly reduced news sharing, but the reductions varied heterogeneously by outlets’ factualness and political slant. On Facebook, content sharing fell relatively more for low-factualness outlets. On Twitter, content sharing fell relatively more for left-wing and high-factualness outlets.

Suggested Citation

  • Daniel Ershov & Juan S. Morales, 2021. "Sharing News Left and Right: The Effects of Policies Targeting Misinformation on Social Media," Carlo Alberto Notebooks 651, Collegio Carlo Alberto.
    • Handle: RePEc:cca:wpaper:651
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    References listed on IDEAS

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    1. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," NBER Working Papers 23089, National Bureau of Economic Research, Inc.
    2. Julia Cage & Nicolas Herve & Beatrice Mazoyer, 2020. "Social Media and Newsroom Production Decisions," Working Papers 20-14, NET Institute.
    3. Pierluigi Conzo & Laura K. Taylor & Juan S. Morales & Margaret Samahita & Andrea Gallice, 2021. "Can ?s Change Minds? Social Media Endorsements and Policy Preferences," Working Papers 202104, School of Economics, University College Dublin.
    4. Morales, Juan S., 2021. "Legislating during war: Conflict and politics in Colombia," Journal of Public Economics, Elsevier, vol. 193(C).
    5. Gordon Pennycook & Ziv Epstein & Mohsen Mosleh & Antonio A. Arechar & Dean Eckles & David G. Rand, 2021. "Shifting attention to accuracy can reduce misinformation online," Nature, Nature, vol. 592(7855), pages 590-595, April.
    6. Ro'ee Levy, 2021. "Social Media, News Consumption, and Polarization: Evidence from a Field Experiment," American Economic Review, American Economic Association, vol. 111(3), pages 831-870, March.
    7. Hunt Allcott & Matthew Gentzkow, 2017. "Social Media and Fake News in the 2016 Election," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 211-236, Spring.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Alexandre De Cornière & Miklos Sarvary, 2023. "Social media news: content bundling and news quality," Post-Print hal-04067655, HAL.
    2. Alexandre de Cornière & Miklos Sarvary, 2023. "Social Media and News: Content Bundling and News Quality," Management Science, INFORMS, vol. 69(1), pages 162-178, January.
    3. Gonzalo Cisternas & Jorge Vásquez, 2022. "Misinformation in Social Media: The Role of Verification Incentives," Staff Reports 1028, Federal Reserve Bank of New York.

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    More about this item

    Keywords

    social media; news sharing; media slant; fake news; misinformation.;
    All these keywords.

    JEL classification:

    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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