# ¶ Text Analysis

Text analysis involves using digital tools and one’s own analytical skills to explore texts, be they literary works, historical documents, scientific literature, or tweets. Approaches can be quantitative (e.g., word counting) and qualitative (e.g., [topic modeling ](https://en.wikipedia.org/wiki/Topic_model)and [sentiment analysis](https://en.wikipedia.org/wiki/Sentiment_analysis)), and tools can range from coding and scripting languages to "out of the box" platforms like [Voyant](https://voyant-tools.org/) and [Lexos](http://lexos.wheatoncollege.edu/upload). 

In the humanities, text analysis is closely associated with the concept of [distant reading](https://walshbr.com/textanalysiscoursebook/book/reading-at-scale/distant-reading/), which essentially means using computational methods to explore and query large (sometimes massive) corpora. The corpa or datasets, as they are more commonly called in the sciences and social sciences, can be structured or unstructured, and the results can have a data visualization component.

**Related Terms:**

* **Text mining** (a term used more in the humanities), **data mining** (a term used more in the sciences and social sciences), and **web scraping** are techniques that use coding, scripting, and "out of the box" tools to gather text and create a corpus (or dataset).<br>


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