Literature mapping data for "Language as Data: A Survey of Natural Language Processing for Economics and Finance"

Data and results for the literature mapping in "Language as Data: A Survey of Natural Language Processing for Economics and Finance". Data used was downloaded from the Web of Science (WoS). The folder WOS has the data and the query used to retrieve it. For drawing the literature map, we used VOSviewer. The folder with same name has the VOSviewer map and network files and the results folder has the figures included in the paper. The paper surveys the main methods, requisites and applications of Natural Language Processing (NLP) in economics and finance, guided by the following research questions: what is NLP currently capable of and how it can contribute to the economic research? What are the methods and techniques to achieve such contributions? What kind of data is needed and suitable for these methods' implementation? And what can we expect to achieve with NLP in economics and finance? These four questions outline the structure of the paper, respectively addressed by the topics of: (i) useful NLP tasks to economics; (ii) NLP models; (iii) economic and financial textual data for NLP; and (iv) NLP applications in economics and finance. We further contribute by resorting to bibliometric tools to help us visualize the literature map of this field, also providing valuable insights to our survey. We finally indicate that there is much room to apply natural language processing to economic issues, but alert that, more than ever, researchers must be careful not to stray away from questions motivated by hypothesis closely tied to economic theories.