Why Software-Driven Text Analysis Matters
Computers can’t think, at least not yet, but they assist human thinking every day whether we our phone’s calculator or answer a random question with a Wikipedia search. What about more complex forms of thought like literary analysis? As it turns out, there are some kinds of software-driven analyses that make useful tools to the human analyst.
Given, say, a novel, what are the most frequently used adjectives? Can you recognize the novel from a wordcloud? What words are likely to appear near each other? What is the text “about” on a semantic level? Does the author have certain habits that reveal themselves numerically? How does this version of a text differ from a previous edition or draft? What do those changes suggest about the writing process or the text’s position in culture?
These are the sorts of questions that computers can help us answer. They can also raise other questions like, “Why have the Yankees been so popular for so long?” Or “Why does ‘Mr’ appear more frequently than ‘Mrs’ in Jane Austen’s novels?”.
- Learn how computers can assist in analyzing literary texts
- Practice using different tools for text analysis
- Learn how to compare and distinguish between different types of software-driven analysis
- Practice applying insights gained through software-driven analysis within a critical interpretation or analysis of a text
- Use Voyant Tools to generate visualizations of a novel you know well, then use it on a novel you haven’t read. Compare your understanding of the results.
- Use Voyant to develop a new argument about a work you know well.
- Use topic modeling to find themes across a number of works by your favorite author.
- Introduction to Data Mining and Text Analysis
- How Not to Read a Victorian Novel
- Distant Reading Duffy
- Chronique Versions Compared
Tools and Data Sets: