Measuring Judicial Sentiment: Methods and Application to US Circuit Courts
提出一种分析司法裁决语言情绪的方法，利用自然语言处理工具从美国上诉法院意见中提取法官对特定社会群体的正面或负面情绪，并利用随机分配法官作为工具变量估计情绪对判决结果和引用的因果影响。
This paper provides a general method for analysing the sentiments expressed in the language of judicial rulings. We apply natural language processing tools to the text of US appellate court opinions to extrapolate judges’ sentiments (positive/good vs. negative/bad) towards a number of target social groups. We explore descriptively how these sentiments vary over time and across types of judges. In addition, we provide a method for using random assignment of judges in an instrumental variables framework to estimate causal effects of judges’ sentiments. In an empirical application, we show that more positive sentiment influences future judges by increasing the likelihood of reversal but also increasing the number of forward citations.