Tools and Methods

Computationally-driven text analysis is utilized in a variety of disciplines and connects humanist scholars to linguists, social scientists, computer scientists, and statisticians. Text analysis looks at elements such as word frequencies, co-occurrence, and statistically generated ‘topics’ to perform ‘distant reading’ of large collections (such as a corpus of Charles Darwin’s letters or 100+ years of BC Historical Newspapers).

Depending on your level of programming skill, you can make use of specialized text analysis libraries in the Python or R programming languages, or use out-of-the-box tools like MALLET and Paper Machines.

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