Text as Data in Python and R

Machine learning is opening new research opportunities across academic disciplines, as it can be used to explore new data types to enrich the current state of the art. In this workshop, we will analyze a text corpus to demonstrate the use of machine learning for natural language processing. In the first half of the workshop, we will provide a basic overview of machine learning, introduce the main concepts and logic of using text as data, and walk through a typical workflow for processing, managing and analyzing a text corpus. We will discuss how to choose between two popular languages in the text analysis domain – Python vs. R – and how to interpret the results from a topic model. Participants who are interested in actively implementing text analysis methods in their own computational work will be invited to attend the second half of the workshop. Here, instructors will demonstrate in two concurrent hands-on tutorials how the topic modelling example from the first half of the course was accomplished in either Python or R. A basic familiarity with the chosen programming language is expected in this half of the workshop. Participants who attend the first part of the workshop will walk away with a basic overview of the capabilities and methods for using text as data. Participants who attend the entire workshop will be equipped with basic programming tools to apply natural language processing in their own research. The workshop will also cover helpful resources for machine learning implementations, such as data sets, storage space, high performance computing, and consultation services at the University of Michigan.

If you have questions about this workshop, please send an email to the instructor at richeym@umich.edu