The materials used in the tutorial are available here.
This tutorial surveys the technology and empirics of text analytics with a focus on finance applications. We present various tools of information extraction and basic text analytics. We survey a range of techniques of classification and predictive analytics, and metrics used to assess the performance of text analytics algorithms. We then review the literature on text mining and predictive analytics in finance, and its connection to networks, covering a wide range of text sources such as blogs, news, web posts, corporate filings, etc. We end with textual content presenting forecasts and predictions about future directions. The tutorial will use the R programming language throughout and present many hands-on examples.
The following major topics will be covered, time permitting:
This tutorial is useful for newbie and advanced R users who are interested in the specic aspects of text mining. Attendees will learn various techniques and terminology related to this area of data science.
Since this will be hands-on, come with your WiFi ready laptop, and work with us as we explain the various concepts. The program files will be made available online at the tutorial. You will need an installation of R of course. RStudio, as always is helpful to have. And if possible, download the packages listed above and install them.
Materials for the tutorial may be downloaded here.