Learning in Networks: An Experiment on Large Networks with Real-World Features
Syngjoo Choi,
Sanjeev Goyal,
Frederic Moisan () and
Yu Yang Tony To
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Frederic Moisan: EM - EMLyon Business School
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Abstract:
"Subjects observe a private signal and make an initial guess; they then observe their neighbors' guesses, update their own guess, and so forth. We study learning dynamics in three large-scale networks capturing features of real-world social networks: Erdös–Rényi, Stochastic Block (reflecting network homophily), and Royal Family (that accommodates both highly connected celebrities and local interactions). We find that the Royal Family network is more likely to sustain incorrect consensus and that the Stochastic Block network is more likely to persist with diverse beliefs. These patterns are consistent with the predictions of DeGroot updating. It lends support to the notion that the use of simple heuristics in information aggregation is prevalent in large and complex networks."
Keywords: social learning; social networks; experimental social science (search for similar items in EconPapers)
Date: 2023-05-01
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Published in Management Science, 2023, 69 (5), 2778-2787 p
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Journal Article: Learning in Networks: An Experiment on Large Networks with Real-World Features (2023) 
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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-04325659
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