Abstract

Large volumes of textual data pose considerable challenges for manual qualitative analysis. We explore semi-automatic coding of textual data by leveraging Natural Language Processing (NLP). We compare the performance of human-developed NLP rules to those inferred by machine learning (ML) algorithms. The results suggest that NLP with ML may be useful to support researchers coding qualitative data.

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