This paper studies the problem of automated classification of fact statements and value statements in written judicial decisions. We compare a range of methods and demonstrate that the linguistic features of sentences and paragraphs can be used to successfully classify them along this dimension. The Wordscores method by Laver et al. (Am Polit Sci Rev 97(2):311–331, 2003) performs best in held out data. In an application, we show that the value segments of opinions are more informative than fact segments of the ideological direction of U.S. circuit court opinions.

中文翻译：

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法院意见中的事实值自动区分

本文研究了书面司法判决中事实陈述和价值陈述的自动分类问题。我们比较了一系列方法，并证明了句子和段落的语言特征可用于成功地沿这个维度对它们进行分类。Laver等人的Wordscores方法。（Am Polit Sci Rev 97（2）：311–331，2003）在保留的数据中表现最佳。在一个应用程序中，我们表明，意见的价值部分比美国巡回法院意见的意识形态方向的事实部分更具信息性。