论文标题
最佳回声室
Optimal Echo Chambers
论文作者
论文摘要
当向他人学习时，人们倾向于将注意力集中在具有相似观点的人上。这通常归因于有缺陷的推理，并被认为会减慢学习和两极分化的信念。但是，我们表明回声室是对信息源准确性的不确定性的合理反应，并且可以改善学习并减少分歧。此外，扩展某人接触的观点范围可能会适得其反，从而减少了他们对他人的信息的反应来减缓他们的学习。我们为选择一组信息源然后从一个信号观察一个信号的贝叶斯决策者建模。由于哪些来源是准确的，因此将注意力集中在接近自己的期望的信号上可能是有益的，因为它们的预期准确性更高。最佳的回声室平衡了类似于自己的观点的信誉与更远的人的用处。
When learning from others, people tend to focus their attention on those with similar views. This is often attributed to flawed reasoning, and thought to slow learning and polarize beliefs. However, we show that echo chambers are a rational response to uncertainty about the accuracy of information sources, and can improve learning and reduce disagreement. Furthermore, extending the range of views someone is exposed to can backfire, slowing their learning by making them less responsive to information from others. We model a Bayesian decision maker who chooses a set of information sources and then observes a signal from one. With uncertainty about which sources are accurate, focusing attention on signals close to one's own expectation can be beneficial, as their expected accuracy is higher. The optimal echo chamber balances the credibility of views similar to one's own against the usefulness of those further away.
