论文标题
假新闻效果：实验中使用信任在新闻中信任来识别积极的推理
The Fake News Effect: Experimentally Identifying Motivated Reasoning Using Trust in News
论文作者
论文摘要
积极的推理认为，人们会扭曲他们如何朝着他们发现有吸引力的信念的方向处理信息。本文创建了一种新颖的实验设计，以确定人们在有先入为主的信念时从贝叶斯更新中进行的积极推理。它分析了受试者如何评估信息源的真实性，这些信息源告诉他们他们的信念分布的中位数太高或太低。贝叶斯人对来源的真实性一无所知，但唤起了积极的信念。证据支持有关移民，收入流动，犯罪，种族歧视，性别，气候变化和枪支法律的政治动机推理。积极的推理有助于解释信念偏见，两极分化和过度自信。
Motivated reasoning posits that people distort how they process information in the direction of beliefs they find attractive. This paper creates a novel experimental design to identify motivated reasoning from Bayesian updating when people have preconceived beliefs. It analyzes how subjects assess the veracity of information sources that tell them the median of their belief distribution is too high or too low. Bayesians infer nothing about the source veracity, but motivated beliefs are evoked. Evidence supports politically-motivated reasoning about immigration, income mobility, crime, racial discrimination, gender, climate change, and gun laws. Motivated reasoning helps explain belief biases, polarization, and overconfidence.
