Abstract
ABSTRACT This Methodologies and Approaches piece argues artificially intelligent machine learning systems can be used to effectively advance justice-oriented research in technical and professional communication (TPC). Using a preexisting dataset investigating patient marginalization in pharmaceuticals policy discourse, we built and tested 49 machine learning systems designed to identify and track rhetorical features of interest. Three popular and one new approach to feature engineering (text quantification) were evaluated. The results indicate that these systems have great potential for use in TPC research.
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