Digital humanities connects literary, historical and cultural questions with computational methods. For example, a researcher might assemble a collection of novels and investigate recurring words, themes and collocations.
A basic Python workflow can involve cleaning text, tokenizing words, normalizing variations and exploring patterns with natural language processing. Such methods can make large bodies of material easier to inspect systematically.
Numerical patterns are not literary interpretations by themselves. The selection of texts, the quality of the data and the historical context still matter. Strong research combines close reading with responsible quantitative analysis.