Abstract
In the information cascade experiment, several subjects sequentially answer a two-choice question, after referring to previous subjects’ choices. Information cascade is defined as a tendency to follow the majority choice, even if, one’s private signal suggests the minority choice. When information cascade occurs, the private signal is lost, and the collective intelligence mechanism does not work. If the majority’s choice is wrong at the onset of the information cascade, it continues to be wrong forever. How can we find the correct choice even when the majority choice is wrong? In this study, we investigate a Bayesian Inference method, which collects private signals in the information cascade, based on the choice behavior of the subjects. Using the empirical data of an experiment, we estimate the probabilistic rule of the choice behavior. We demonstrate that the Bayesian algorithm works and one can know the correct choice even if the majority’s choice is wrong.
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References
Wang, T., Wang, D.: Why Amason’s ratings might mislead you. Big Data 2, 196 (2014)
Rendell, L., Boyd, R., Cownden, D., Enquist, M., Eriksson, K., Feldman, M.W., Fogarty, L., Ghirlanda, S., Lillicrap, T., Laland, K.N.: Why copy others? Insights from the social learning strategies tournament. Science 328, 208 (2010)
Nakayama, K., Hisakado, M., Mori., S.: Nash equilibrium of social-learning agents in a restless multiarmed bandit game. Sci. Rep. 7 (2017). Article number: 1937
Bikhchandani, S., Hirshleifer, D., Welch, I.: A theory of fads, fashion, custom, and cultural change as information cascades. J. Polit. Econ. 100, 992–1026 (1992)
Devenow, A., Welch, I.: Eur. Econ. Rev. 40, 603–615 (1996)
Surowiecki, J.: The Wisdom of Crowds. Doubleday, New York (2004)
Page, S.E.: The Difference. Princeton University Press, Princeton (2007)
Hino, M., Irie, Y., Hisakado, M., Takahashi, T., Mori, S.: Detection of phase transition in generalized Póla urn in information cascade experiment. J. Phys. Soc. Jpn. 85(3), 034002–034013 (2016)
Mori, S., Hisakado, M.: Information cascade experiment: Urn Quiz. In: Sato, A.H. (ed.) Applications of Data-Centric Science to Social Design. Agent-Based Social Systems, vol. 14, pp. 181–191. Springer, Singapore (2016)
Anderson, L., Holt, C.: Information cascades in the laboratory. Am. Econ. Rev. 87(5), 847–862 (1997)
Mori, S., Hisakado, M., Takahashi, T.: Phase transition to two-peaks phase in an information cascade voting experiment. Phys. Rev. E 86, 026109 (2012)
Goeree, J.K., Palfrey, T.R., Rogers, B.W., McKelvey, R.D.: Self-correcting information Cascades. Rev. Econ. Stud.74, 733–762 (2007)
Eguíluz V.M., Masuda, N., Fernández-Gracia, J.: Bayesian decision making in human collectives with binary choices. PLoS One 10(4), e0121332 (2015). https://doi.org/10.1371/journal.pone.0121332
Hisakado M., Mori S.: Information cascade and bayes formula. In: Sato, A.H. (ed.) Applications of Data-Centric Science to Social Design. Agent-Based Social Systems, Chapter 12, vol. 14, pp. 193–202. Springer, Singapore (2019)
Hill, B., Lane, D., Sudderth, W.: A strong law for some gener-alized urn processes. Ann. Prob. 8, 214–226 (1980)
Mori, S., Hisakado, M.: Correlation function for generalized Polya urns: finite-size scaling analysis. Phys. Rev. E92, 052112 (2015)
Mori, S., Hisakado, M.: Finite-size scaling analysis of binary stochastic processes and universality classes of information cascade phase transition. J. Phys. Soc. Jpn. 84, 054001 (2015)
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Takeda, K., Hisakado, M., Mori, S. (2020). How to Collect Private Signals in Information Cascade: An Empirical Study. In: Masuda, N., Goh, KI., Jia, T., Yamanoi, J., Sayama, H. (eds) Proceedings of NetSci-X 2020: Sixth International Winter School and Conference on Network Science. NetSci-X 2020. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-38965-9_14
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DOI: https://doi.org/10.1007/978-3-030-38965-9_14
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