Voyant Tools is a web-based text reading and analysis environment. It is a scholarly project that is designed to facilitate reading and interpretive practices for digital humanities students and scholars as well as for the general public.
This web-based software compares two text files to calculate the similarity between them.
The tidytext R package uses the design philosophy of the popular tidyverse package ecosystem in R and applies it to common textual analysis tasks.
This is the CRAN Task View for natural language processing. You can use it to find links to a multitude of R packages that can be used to process and analyze text.
Python's Natural Language Toolkit is among the most popular packages for working with textual data in Python. It provides the access to libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, among other tasks.
There are many ways to apply text analysis. You can use software like Voyant or learn to code with Python or R.
Choosing to use a programming language will provide you with far more flexibility than offered by any existing software applications. And Python is the most widely used programming language for text analysis.
If you are new to Python and Text Analysis, a great resource to begin with is Melanie Walsh's free, online book, Introduction to Cultural Analytics and Python (2021). In this book you can learn how to get started with Python (Ch. 1), store data (including texts) in data tables known as dataframes (Ch. 2), and perform some basic text analysis (Ch. 5). This book even allows you to interactively work with her code if you click the Binder (rocket) logo at the top of the screen.
1. The Programming Historian (over 100 DH lessons in English, including various on text analysis, as well as dozens of lessons in French, Spanish, and Portuguese).
2. The NLTK Book (aka. Natural Language Processing with Python) - NLTK is one of the most popular Natural Language Processing (NLP) Python packages and almost certainly is the most popular for text analysis learners.
If you start the lessons above and feel you need to start with the basics in Python, a great resource are the Software Carpentry tutorials (available online or you can sign up for in-person Software Carpentry the next time we host it).
