Abstract
In this lesson you will first learn what topic modeling is and why you might want to employ it in your research. You will then learn how to install and work with the MALLET natural language processing toolkit to do so.
Highlights
This lesson requires you to use the command line
If you have no previous experience using the command line you may find it helpful to work through the Programming Historian Bash Command Line lesson
(We would like to thank Robert Nelson and Elijah Meeks for hints and tips in getting MALLET to run for us the first time, and for their examples of what can be done with this tool.)
Summary
In this lesson you will first learn what topic modeling is and why you might want to employ it in your research. You will learn how to install and work with the MALLET natural language processing toolkit to do so. We will run the topic modeller on some example files, and look at the kinds of outputs that MALLET installed. This will give us a good idea of how it can be used on a corpus of texts to identify topics found in the documents without reading them individually. (We would like to thank Robert Nelson and Elijah Meeks for hints and tips in getting MALLET to run for us the first time, and for their examples of what can be done with this tool.)
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