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Title:Semi-Automatic Content Analysis of Qualitative Data
Author(s):Yan, Jasy Liew Suet; McCracken, Nancy; Crowston, Kevin
Subject(s):natural language processing
qualitative research methods
semi-automatic content analysis
machine learning
active learning
Abstract:Qualitative content analysis is commonly used by social scientists to understand the practices of the groups they study, but it is often infeasible to manually code a large text corpus within a reasonable time frame and budget. To address this problem, we are building a software tool to assist social scientists performing content analysis. We present our semi-automatic system that leverages natural language processing (NLP) and machine learning (ML) techniques for initial automatic coding, which human coders then review and correct. Through active learning, these human-verified annotations are subsequently used to train a higher performing model for machine annotation. We discuss design strategies adopted to optimize the system performance.
Issue Date:2014-03-01
Publisher:iSchools
Citation Info:Yan, J. L. S., McCracken, N., & Crowston, K. (2014). Semi-Automatic Content Analysis of Qualitative Data. In iConference 2014 Proceedings (p. 1128 - 1132). doi:10.9776/14399
Series/Report:iConference 2014 Proceedings
Genre:Conference Poster
Type:Text
Language:english
URI:http://hdl.handle.net/2142/47333
DOI:https://doi.org/10.9776/14399
Other Identifier(s):399
Publication Status:published
Peer Reviewed:yes
Rights Information:Copyright 2014 is held by the authors of individual items in the proceedings. Copyright permissions, when appropriate, must be obtained directly from the authors.
Date Available in IDEALS:2014-02-28


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