Analyzing Financial Text Data for Research

The chapter covers various types of data used in research, including financial statement data and unique non-standard data sources like scraped text for textual analysis. It discusses challenges faced in dealing with unclean data and emphasizes the importance of data cleaning quality in research outcomes. The chapter explores techniques for analyzing financial text data, such as word counts, sentiment analysis, vectorizing texts, and utilizing models like supervised learning for classification.