A general analysis of boundedly rational learning in social networks
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- Mueller-Frank, Manuel, 2014. "Does one Bayesian make a difference?," Journal of Economic Theory, Elsevier, vol. 154(C), pages 423-452.
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- Alex Centeno, 2022. "A Structural Model for Detecting Communities in Networks," Papers 2209.08380, arXiv.org, revised Oct 2022.
- Abhijit Banerjee & Olivier Compte, 2024.
"Consensus and Disagreement: Information Aggregation under (Not So) Naive Learning,"
Journal of Political Economy, University of Chicago Press, vol. 132(8), pages 2790-2829.
- Abhijit Banerjee & Olivier Compte, 2022. "Consensus and Disagreement: Information Aggregation under (not so) Naive Learning," NBER Working Papers 29897, National Bureau of Economic Research, Inc.
- Abhijit Banerjee & Olivier Compte, 2023. "Consensus and Disagreement: Information Aggregation under (not so) Naive Learning," Papers 2311.08256, arXiv.org.
- Mueller-Frank, Manuel, 2024. "As strong as the weakest node: The impact of misinformation in social networks," Journal of Economic Theory, Elsevier, vol. 215(C).
- Li, Wei & Tan, Xu, 2021. "Cognitively-constrained learning from neighbors," Games and Economic Behavior, Elsevier, vol. 129(C), pages 32-54.
- Miguel Risco & Manuel Lleonart-Anguix, 2024. "Feed for good? On the effects of personalization algorithms in social platforms," CRC TR 224 Discussion Paper Series crctr224_2024_580, University of Bonn and University of Mannheim, Germany.
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More about this item
Keywords
Social networks; naive inference; information aggregation; bounded rationality; agreement;All these keywords.
JEL classification:
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
- D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
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