美联储：制造业情绪：用文本分析预测工业生产（英文版）

This paper examines the link between industrial production and the sentiment expressed in natural language survey responses from U.S. manufacturing firms. We compare several natural language processing (NLP) techniques for classifying sentiment, ranging from dictionary-based methods to modern deep learning methods. Using a manually labeled sample as ground truth, we find that deep learning models—partially trained on a human-labeled sample of our data—outperform other methods for classifying