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.
Original language | English (US) |
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Journal | Proceedings of the ASIST Annual Meeting |
Volume | 47 |
DOIs | |
State | Published - Nov 2010 |
Keywords
- Machine learning
- Natural language processing
- Qualitative data analysis
ASJC Scopus subject areas
- Information Systems
- Library and Information Sciences