Let’s pick up where we left off yesterday and do some more exploration with text mining. Like yesterday we’ll use the tidytext package for R. And we’ll lean heavily on Julie Silge and David Robinson’s Text Mining with R. Data We’ll turn again to the Federal Reserve for our text data. But today we’ll explore the Beige Book, which gathers anecdotal information on current economic conditions across the Federal Reserve Districts.
Textmining is an exciting topic. There is tremendous potential to gain insights from textual analysis. See for example Gentzko, Kelly and Taddy’s Text as Data. While text mining may be quite advanced in other fields, in finance and economics the application of these techniques is still in its infancy. In order to take advantage of text as data, economists and financial analysts need tools to help them. Fortunately, there is a great resource: Text Mining with R by Julia Silge (blog and on Twitter atjuliasilge) and David Robinson (blog and on Twitter atdrob).