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Disengaging from Reality Online Behavior and Unpleasant Political News

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  • D'Amico, Leonardo
  • Tabellini, Guido

Abstract

Why, in the face of scandals and misbehaviors, do partisan supporters hardly change their minds about their favored candidates? We study individuals’ online engagement with negative news on candidates in the 2016 US Presidential Election. Compared to independents, partisan users avoid commenting bad news on their favorite candidate, but seek them on its opponent, a political “ostrich effect†. When they do comment on bad news about their candidate, they try to rationalize them, display a more negative sentiment, and are more likely to cite scandals of the opponent. This behavior is consistent with the predictions of a model of online interactions where paying attention to non-consonant news is emotionally or psychologically costly, while paying attention to consonant ones is pleasing. Because users enjoy receiving positive feedback on their views, intrinsic biases that drive ideological segregation are amplified on social media.

Suggested Citation

  • D'Amico, Leonardo & Tabellini, Guido, 2022. "Disengaging from Reality Online Behavior and Unpleasant Political News," CEPR Discussion Papers 17210, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:17210
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    Cited by:

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    2. Marco Manacorda & Guido Tabellini & Andrea Tesei, 2022. "Mobile internet and the rise of political tribalism in Europe," CEP Discussion Papers dp1877, Centre for Economic Performance, LSE.
    3. Jean-Michel Benkert, Ludmila Matyskova, Egor Starkov, 2024. "Strategic Attribute Learning," Diskussionsschriften dp2411, Universitaet Bern, Departement Volkswirtschaft.
    4. Marco Manacorda & Guido Tabellini & Andrea Tesei, 2022. "Mobile Internet and the Rise of Communitarian Politics," CESifo Working Paper Series 9955, CESifo.
    5. Guy Aridor & Rafael Jiménez-Durán & Ro'ee Levy & Lena Song, 2024. "The Economics of Social Media," Journal of Economic Literature, American Economic Association, vol. 62(4), pages 1422-1474, December.
    6. Jean-Michel Benkert & Ludmila Matyskova & Egor Starkov, 2024. "Strategic Attribute Learning," Papers 2412.10024, arXiv.org, revised Nov 2025.

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