Word frequency analysis is a research method focused on identifying patterns and trends in unstructured texts. It is sometimes referred to as "text mining".
Voyant is text mining software recommended for beginners just starting to experiment with text mining and its uses. It is not very robust, but it is an easy-to-access starting point.
AntConc is a more robust text mining app for identifying word frequencies, concordance, comparative textual analysis, and more. It is downloadable for free from the creator's website, and is available for Macbook, Windows, and Linux machines.
Mallet is a text mining software often used for topic modeling, or identifying themes across a text. The software is downloadable for free from the developers' website.
For advanced text mining techniques such as sentiment analysis or named entity recognition, researchers usually need to code a text mining environment. Python and R are commonly used programming software for text mining.
This workshop recording provides a general overview of text mining methods and software, as well as library and campus resources available to support text mining research.
The library has created a series of tutorials about how to use the text mining software AntConc, including how to download it, how to upload a corpus, and how to use several of its major tools.