Ranking for Engagement: How Social Media Algorithms Fuel Misinformation and Polarization
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Cited by:
- George Beknazar-Yuzbashev & Rafael Jiménez-Durán & Jesse McCrosky & Mateusz Stalinski, 2025. "Toxic Content and User Engagement on Social Media: Evidence from a Field Experiment," CESifo Working Paper Series 11644, CESifo.
- Beknazar-Yuzbashev, George & Jiménez-Durán, Rafael & McCrosky, Jesse & Stalinski, Mateusz, 2025. "Toxic Content and User Engagement on Social Media: Evidence from a Field Experiment," CAGE Online Working Paper Series 741, Competitive Advantage in the Global Economy (CAGE).
- Beknazar-Yuzbashev, George & Jiménez-Durán, Rafael & McCrosky, Jesse & Stalinski, Mateusz, 2025. "Toxic Content and User Engagement on Social Media : Evidence from a Field Experiment," The Warwick Economics Research Paper Series (TWERPS) 1543, University of Warwick, Department of Economics.
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More about this item
Keywords
social media; recommendation algorithm; ranking algorithm; feedback loop; engagement; misinformation; polarization; popularity ranking; algorithmic gatekeeper;All these keywords.
JEL classification:
- D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
- L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media
- L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
NEP fields
This paper has been announced in the following NEP Reports:- NEP-MIC-2022-11-28 (Microeconomics)
- NEP-PAY-2022-11-28 (Payment Systems and Financial Technology)
- NEP-SOC-2022-11-28 (Social Norms and Social Capital)
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