Machine learning and rule-based automated coding of qualitative data

Kevin Crowston; Xiaozhong Liu; Eileen E. Allen

doi:10.1002/meet.14504701328

Machine learning and rule-based automated coding of qualitative data

Kevin Crowston, Xiaozhong Liu, Eileen E. Allen

School of Information Studies

Research output: Contribution to journal › Article › peer-review

32 Scopus citations

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)
Journal	Proceedings of the ASIST Annual Meeting
Volume	47
DOIs	https://doi.org/10.1002/meet.14504701328
State	Published - Nov 2010

Keywords

Machine learning
Natural language processing
Qualitative data analysis

ASJC Scopus subject areas

Information Systems
Library and Information Sciences

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10.1002/meet.14504701328

Cite this

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title = "Machine learning and rule-based automated coding of qualitative data",

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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Machine learning and rule-based automated coding of qualitative data

Abstract

Keywords

ASJC Scopus subject areas

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