Machine Learning and Rule-Based Automated Coding of Qualitative Data

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Abstract:

Researchers often employ qualitative research approaches but large volumes of textual data pose considerable challenges to manual coding. In this research, we explore how to implement fully or semi-automatic coding on textual data (specifically, electronic messages) by leveraging Natural Language Processing (NLP). In particular, we compare the performance of human-developed NLP rules to those inferred by machine learning algorithms. The experimental results suggest that NLP with machine learning can be an effective way to assist researchers in coding qualitative data.