How to Collect Private Signals in Information Cascade: An Empirical Study
How to Collect Private Signals in Information Cascade: An Empirical Study
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如何收集信息级联中的私有信号：实证研究
DOI：
10.1007/978-3-030-38965-9_14
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
K. Takeda,M. Hisakado and S.Mori
中科院分区：
文献类型：
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作者：
K. Nakayama;R. Nakamura;M. Hisakado;and S.Mori;K. Takeda,M. Hisakado and S.Mori
在信息级联实验中，几个被试参照前一个被试的选择顺序回答一个选择题。信息级联被定义为一种倾向于跟随多数人的选择，即使一个人的私人信号暗示了少数人的选择。当信息级联发生时，私有信号丢失，集体智能机制不起作用。如果大多数人的选择在信息级联开始时是错误的，那么它将永远是错误的。即使大多数选择是错误的，我们如何找到正确的选择？在本研究中，我们研究了一种贝叶斯推理方法，该方法基于被试的选择行为，在信息级联中收集私人信号。利用实验的经验数据，估计了选择行为的概率规律。我们证明了贝叶斯算法是有效的，即使大多数人的选择是错误的，人们也可以知道正确的选择。
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.