user2016

This tutorial surveys the technology and empirics of text analytics with a focus on nance applications. We present various tools of information extraction and basic text analytics. We survey a range of techniques of classication 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 nance, and its connection to networks, covering a wide range of text sources such as blogs, news, web posts, corporate lings, 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.

For details, refer to tutorial description.